. "Physics"@en . . "Computer Science"@en . . "Astronomy"@en . . "English"@en . . "Atmospheric Science"@en . . "Mathematics"@en . . "Modern astrostatistics"@en . . "3" . "Randomness, uncertainties and deviations from the norm surround us in everyday life. A major asset of any scientist is to see beyond the complexity of noise, scatter and biases, and to find an underlying -often surprisingly simple- explanation for the noisy data. This course is specialized to astronomical data analysis, but the topics discussed will also foster an improved understanding of Google, Facebook and other free social media services.\n\nTopics that will be covered include:\n\nDescriptive statistics: Finding meaning in a huge data set.\nInference statistics: Constraining a physical model by data.\nFiltering, e.g. for gravitational wave detections and source detection.\nRandom fields: Sky surveys and structure formation in cosmology.\nSampling methods: Making huge data analyses numerically feasible.\nBayesian Hierarchical Models: How to disentangle a seemingly complex analysis.\nPrior Theory and Information Measures: How not to hide prejudices in an analyses.\nMissing data and elusive physics: What to do if your sought signal hides in the dark figures?\nMachine learning: Finding patterns which escape humans.\n\nOutcome:\nPrincipal course objective: After completion of this course, you will be able to correctly interpret noisy data. You will be able to design and apply statistical methods to answer scientific questions. You will be able to measure parameters, discover astronomical objects, or discover elusive signals in noisy data.\n\nUpon completion of this course, you will be able to:\n\nRecognize the most common distributions of noisy astronomical data\nIdentify signals in noisy data\nReject theories which are incompatible with data\nDesign own statistical methods to analyze complex data\nCategorize astronomical objects\nSolve simple Bayesian Hierarchical Models\nDiscover prejudices in analyses\nExplain basic machine learning algorithms" . . "Presential"@en . "TRUE" . . "Origin and evolution of the universe"@en . . "6" . "This course introduces the theoretical underpinnings and the observational evidence for modern cosmology.\r\n\r\nAfter reviewing the evidence for the hot Big Bang model, we study the basics of relativistic cosmology and the expansion history. We then discuss the measurement of cosmological parameters, dark matter and dark energy. Next we study the thermal history and physical processes occurring in the early universe, such as inflation, Big Bang nucleosynthesis and recombination.\r\n\r\nThis course covers the following topics:\r\nCosmic kinematics and dynamics\r\nMeasurement of cosmological parameters\r\nDark matter\r\nThermal history of the Universe\r\nCosmic microwave background anisotropies\r\nInflation\n\nOutcome:\nUpon completion of this course you will be able to describe the current cosmological model and the observational evidence supporting this. Moreover, you will be able to do relevant calculations and read the scientific literature on the topic.\r\n\r\nUpon completion of this course you will be able to:\r\n\r\nExplain the basics of the current cosmological model\r\nUse the Friedmann equations to calculate quantities in an expanding Universe\r\nExplain how cosmological parameters are measured\r\nDiscuss the need for non-baryonic dark matter\r\nExplain various milestones in the thermal history, including Big Bang nucleosynthesis, neutrino decoupling, recombination and photon decoupling\r\nInterpret observations of the Cosmic Microwave Background\r\nExplain how inflation solves the problems with the Big Bang model" . . "Presential"@en . "TRUE" . . "Large scale structure and galaxy formation"@en . . "6" . "How galaxies and the large-scale structures in which they are embedded form is a fundamental question in extra-galactic astronomy. It is an area that has seen tremendous progress, but is still constantly challenged by ever-improving observational data. This course introduces you to this fascinating subject and the underlying physics, starting from how small density perturbations grow into dark matter haloes, to how baryons cool and form the galaxy population we observe today.\n\nPhysical concepts are derived from basic principles where possible. The emphasis is on intuitive rather than mathematically rigorous derivations.\n\nTopics that will be covered include:\n\nLinear growth of density perturbations\nFree streaming\nTransfer functions and the matter power spectrum\nNon-linear spherical collapse\nJeans smoothing\nRadiation drag\nStatistical cosmological principle\nClustering and biasing\nHalo mass functions and Press-Schechter theory\nScaling laws and virial relations\nCosmic web\nRedshift-space distortions\nRadiative cooling and its importance\nAngular momentum and its influence\nReionization\nThe Gunn-Peterson effect\nThe thermal history of the intergalactic medium\nFeedback processes\nHalo models, semi-empirical models, and simulations\n\nOutcome:\nUpon completion of this course you will be able to explain how (we think that) large-scale structures and galaxies form and evolve and you will be able to carry out calculations of the formation of structures in the universe.\r\n\r\nUpon completion of the course you will be able to:\r\n\r\nCompute the growth of density fluctuations\r\nCompute the shape of the matter power spectrum\r\nExplain the morphology of the cosmic web\r\nExplain redshift-space distortions\r\nExplain galaxy biasing and clustering\r\nCompute halo mass functions using Press-Schechter theory\r\nCompute galaxy and halo scaling relations\r\nUnderstand radiative cooling processes\r\nEstimate the effect of radiative cooling on galaxy formation\r\nEstimate the effect of angular momentum on galaxy formation\r\nModel the process of reionization\r\nCompute the thermal history of the intergalactic medium\r\nCompute Gunn-Peterson absorption\r\nUnderstand the basics of feedback processes in galaxy formation\r\nUnderstand the basics of halo models, semi-empirical models and simulations of galaxy formation" . . "Presential"@en . "TRUE" . . "Stellar structure and evolution"@en . . "6" . "Stellar observations and the quest for understanding stars have always been at the core of astronomy since ancient times. Stars are not only extraordinary physics laboratories, but they are also vital to our understanding of the life cycle of systems at all scales, such as planets, galaxies and the intergalactic medium. In this course, you will first learn the basic physics of stellar structure in all relevant physical regimes. Then, we will follow a journey through a star’s life where its structure changes as a function of time. We will only focus on isolated stars.\n\nOutcome:\nAfter completion of this course, you will be able to answer quantitative and qualitative questions about a star’s interior structure and life path, when considering an isolated star, ignoring magnetic fields and rotation.\r\n\r\nThis means that after this course you will be able to:\r\n\r\nRun and process the output of the MESA stellar evolution code\r\nRecognise a star’s evolution stage from its observational appearance\r\nName the main uncertainties in the current knowledge of stellar structure and evolution\r\nWrite a clear and professional scientific report" . . "Presential"@en . "TRUE" . . "Interstellar medium"@en . . "6" . "The space between the stars is filled with matter, magnetic fields, and radiation. This course describes this ‘interstellar medium’ as an an integral part of galactic ‘ecosystems’. It provides an overview of the known constituents of the ISM (ionized, atomic, and molecular gas; dust; magnetic fields; cosmic rays; EM radiation), and the different environments in which these are encountered (the 2- and 3-phase models of the ISM) along with the observational diagnostics (atomic and molecular spectroscopy; spectral energy distributions).\r\n\r\nIt discusses the physical processes that govern the interactions within the ISM and with stars (energy balance; shocks). And it highlights the relationships between the ISM and stars and their host galaxies (birth and death of stars; supernovae; nuclei of active galaxies).\n\nOutcome:\nThe student will gain relevant background information and hands-on experience that will enable him/her to follow the current literature on the interstellar medium and to do research in this field." . . "Presential"@en . "TRUE" . . "Star and planet formation"@en . . "6" . "The student will gain relevant background information and hands-on experience that will enable him/her to follow the current literature on the interstellar medium and to do research in this field.\n\nOutcome:\nThe student will gain up-to-date insight into one of the fastest growing research areas in astronomy. The course will provide sufficient background to be able to follow the current literature on star- and planet formation and to do research in this field or in a neighboring field (e.g., star formation in external galaxies or on cosmological scales)." . . "Presential"@en . "TRUE" . . "Advances in data mining"@en . . "6" . "The traditional data mining techniques are mainly focused on solving classification, regression and clustering problems. However, the recent developments in ICT led to the emergence of new sorts of massive data sets and related data mining problems. Consequently, the field of data mining has rapidly expanded to cover new areas of research, such as:\r\n\r\nprocessing huge (tera- or petabytes big) data sets\r\nreal-time analysis of data streams (internet traffic, sensor data, electronic transactions, etc.),\r\nsearching for similar pairs of objects such as texts, images, songs, etc., in huge collections of such objects,\r\nfinding anomalies in data,\r\nclustering of massive sets of records,\r\nrecommendation systems,\r\nreduction of data dimensionality\r\napplications of DeepLearning to data mining\r\n\r\nDuring the course you will learn several techniques, algorithms and tools for addressing these new and challenging data mining problems:\r\n\r\nRecommender Systems: Collaborative Filtering, MatrixFactorization\r\nAlgorithms for dimensionality reduction: LLE, t-SNE, UMAP\r\nRandomForest and XGBoost: the most popular algorithms for classification and regression trees\r\nAlgorithms for detecting anomalies in data\r\nLocality Sensitive Hashing (LSH): a general technique for finding similar items in huge collections of items\r\nAlgorithms for mining data streams: sampling, filtering (Bloom filters), probabilistic counting\r\nApplications of DeepLearning to data mining\r\nDistributed Processing of Massive Data: Hadoop, MapReduce, Spark\n\nOutcome:\nAfter completing the course, the students should:\r\n\r\nknow most successful algorithms and techniques used in Data Mining;\r\ngain some hands-on experience with several algorithms for mining complex data sets;\r\nbe able to apply the acquired knowledge and skills to new problems." . . "Presential"@en . "TRUE" . . "Introduction to deep learning"@en . . "6" . "The course provides an introduction to key concepts, architectures, and algorithms for Deep Learning and its applications. It covers the following topics:\r\n\r\nPart One: Multilayer Peceptron and Backpropagation\r\n\r\nFrom a Single Layer Perceptron to Deep Learning: a historical perspective\r\nAlgorithms for training MLPs: Stochastic Gradient Descent and its variants; Backpropagation\r\nAlternative activation and loss functions; Initialization, Regularization, Dropout, Batch Normalization\r\nIntroduction to GPU-computing, Keras, TensorFlow; Hyperparameter Tuning\r\n\r\nPart Two: Deep Learning for computer vision and language processing\r\n\r\nConvolutional Networks: key architectures and applications; Transfer Learning\r\nRecurrent Networks: from Backpropagation Through Time to Attention Mechanism and Transformers\r\n\r\nPart Three: Generative Networks\r\n\r\nAutoencoders\r\nGenerative Adversarial Networks (GAN's)\r\nDiffusion Models\r\n\r\nDuring the course several state-of-the-art applications of Deep Learning to image recognition, computer vision, language modeling, game playing programs, etc., will be discussed. The course consists of weekly lectures, three programming assignments (in Python, TensorFlow) and the final written exam.\n\nOutcome: Not Provided" . . "Presential"@en . "TRUE" . . "Simulation and modeling in astrophysics (amuse)"@en . . "6" . "During this course you will learn how to perform research with existing computational tools and simulation codes. This will be done using the Astrophysics Multipurpose software Environment (AMUSE) software. You will learn how to set up a computer experiment, write the code to carry out the simulations, perform the calculations, collect and analyze the data, and critically assess the results.\n\nStudents, in groups of two or three, will work on their joined projects, and report on the results by written report and a presentation.\n\nThe final project is chosen in discussion with the teacher from a wide range of topics. From a computational point of view the topic should generally include at least two fundamental physical phenomena:\ngravitational dynamics, hydrodynamics, radiative transfer, or stellar astrophysics.\n\nThe work will be carried out using AMUSE to perform a number of simulations to study astrophysical phenomena. The course ends with a presentation and report on the final project.\n\nOutcome: Not Provided" . . "Presential"@en . "FALSE" . . "Numerical recipes in astrophysics"@en . . "6" . "In this course you will learn how and why some of the most powerful and broadly used algorithms in astrophysics work and gain a deeper understanding of numerical methods.This will allow you to identify the right tool for the job for whatever computational problem you may encounter in astrophysics, and to program more effectively, whether you are fitting data, sampling a distribution, integrating orbits or optimizing your computational model.\r\n\r\nDuring the lectures we will discuss numerics and consider and derive specific algorithms that are useful in astrophysics. During the problem classes students will work together on applying this knowledge to a computational problem through coding.\n\nOutcome:\nIn specific, after this course, you will be able to:\r\n\r\nEvaluate the outcomes of computational codes\r\nConstruct an efficient computer program\r\nSolve a wide array of astrophysical problems" . . "Presential"@en . "TRUE" . . "Reinforcement learning"@en . . "6" . "Deep reinforcement learning is a field of Artificial Intelligence that has attracted much attention since impressive achievements in Robotics, Atari, and most recently Go, where human world champions were defeated by computer players. These results build upon a combination of the rich history of reinforcement learning research and deep learning.\r\nThis course teaches the field of deep reinforcement learning: How does it work, why does it work, and what are the reinforcement learning methods on which Robotics and AlphaGo’s success are based? By the end of the course you should have acquired a good understanding of the field of deep reinforcement learning.\r\n\r\nThe defining characteristic of reinforcement learning is that agents learn through interaction with an environment, not unlike humans learn by doing. Instead of telling a learner which action to take, the agent analyzes which action to take so as to maximize a reward signal. Reinforcement learning is a powerful technique for solving sequential decision problems.\r\n\r\nThe defining characteristic of deep learning is that the model generalizes, it build a hierarchy of abstract features from its inputs.\r\n\r\nProminent reinforcement learning problems occur, amongst others, in games and robotics. In this course you will learn the necessary theory to apply reinforcement learning to realistic problems from the field of computer game playing.\n\nThe following topics and algorithms are planned to be discussed:\r\n\r\nTabular Value-based Reinforcement Learning, such as Q-learning\r\nDeep Value-based Reinforcement Learning, such as DQN\r\nPolicy-based Reinforcement Learning, such as PPO\r\nModel-based Reinforcement Learning\r\nTwo-Agent Self-Play (AlphaGo)\r\nMulti-Agent Reinforcement Learning (Poker, StarCraft)\r\nHierarchical Reinforcement Learning\r\nMeta-Learning, such as MAML\r\nBrief Summary of Deep Supervised Learning\r\n\r\nIn addition the role of reinforcement learning in artificial intelligence and the relation with psychology will be discussed (human learning).\r\nThis a hands-on course, in which you will be challenged to build working game playing programs with different reinforcement learning methods. This is a challenging course in which proficiency in Python and deep learning libraries (such as Keras and PyTorch) is important.\r\nAll assignments should be made in Python.\n\nOutcome:\nAfter completing the reinforcement learning course, the students should be able to:\r\n\r\nUnderstand the key features and components of deep reinforcement learning;\r\nKnowledge of theoretical foundations on basic and advanced deep reinforcement learning techniques;\r\nUnderstand the scientific state-of-the-art in the field of deep reinforcement learning." . . "Presential"@en . "TRUE" . . "Seminar advances in deep learning"@en . . "6" . "In recent years we have witnessed an explosion of research, development, and applications of Deep Learning. The main objective of this course is to provide a wide overview of the current state of this area and to focus on a few, carefully selected topics, covering them in depth by studying and presenting most relevant papers, and doing own research on these selected topics. This research will have a form of producing new experimental results, testing new algorithms or theories and documenting findings in scientific reports. The best reports can be submitted to conferences or published as research papers.\r\n\r\nDuring the course students will work (in small teams) on selected topics/problems, performing experiments on GPU-computers, reporting on their progress during weekly meetings. Each team will have to summarize their work in a final presentation and a project report.\n\nOutcome:\nDuring the course students will:\r\n\r\ngain an overall picture of the recent developments in Deep Learning,\r\nidentify some promising research directions,\r\ngain some hands-on research experience, including studying related papers, identifying research problems, inventing solutions of these problems, verifying their ideas by experimenting and documenting findings in a scientific style,\r\nlearn to work together is small research teams,\r\nlearn to prepare and give presentations,\r\nlearn to write scientific reports." . . "Presential"@en . "TRUE" . . "Astronomical telescopes and instruments"@en . . "6" . "This course will teach Astronomy and Physics master's students the foundations of modern optical instruments including advanced concepts in geometrical and physical optics, optical design, and instrumentation. The course is the cornerstone of the Astronomy and Instrumentation master's specialisation. For students who have NOT followed the Astronomy bachelor's course Astronomical Observing Techniques (AOT) it is mandatory to follow the AOT crash-course during the first week, as indicated in the Astronomy master schedules.\n\nThe following topics will be covered in lectures and exercises:\n\nFoundations of optics\nInterference, diffraction and Fourier optics\nGeometrical optics\nPolarization\nThin films and coatings\nOptical design\nTelescopes\nImagers\nClassical spectrographs\nAdvanced spectrographs\nInterferometers\nPolarimeters\n\nOutcome:\nStudents will be able to:\r\n\r\nUnderstand the principles of modern optical instruments in astronomy\r\nExplain the operations of state-of-the-art optical instruments\r\nDesign simple astronomical instruments" . . "Presential"@en . "TRUE" . . "Detection of light a"@en . . "3" . "Part a of this course is aimed at observational astronomers in general, to provide a solid knowledge basis on the generation of their observational data. Detectors are the crucial link between the astronomical target and the observer. Apart from the telescope, their performance is arguably the single most important component – and often weakest link – in the chain of observational optical devices. As astronomers are increasingly aiming at fainter targets, the quality and calibration of the detector systems have become increasingly important. Detector types that will be discussed include intrinsic and extrinsic photo-conductors, CCDs, BIB detectors, photodiodes, bolometers, and submillimeter- and millimeterwave heterodyne receivers. The course covers their physical principles and discusses performance aspects like linearity and dynamical range, spectral response, bandwidth, quantum efficiency and noise. In addition, this course covers practical aspects of general relevance to observational astronomers, including readout schemes, cosmetic quality of array detectors and the mitigation of artefacts.\n\nOutcome: Not Provided" . . "Presential"@en . "TRUE" . . "Detection of light b"@en . . "3" . "Part b of this course covers recent detector technologies, such as:\n\nMicrowave kinetic inductance detectors (MKIDs)\nTransition edge sensors (TES)\nAvalanche photodiodes\nDetection of high energy photons\nQuantum well infrared photodetector (QWIP)\n\nThe emphasis of part b is on applications and technical realization. Since the lectures will be given by external guest lecturers, the topics covered in this course may change, depending on their availability.\n\nOutcome: Not Provided" . . "Presential"@en . "TRUE" . . "Radio astronomy"@en . . "6" . "In this course you learn critical aspects of radio astronomy, allowing you to relate radio observations to the astrophysical sources they probe. We thus deal with both the electromagnetic processes in the Universe that produce radio emission, as well as the workings of the telescopes that measure this radio emission.\nThe course consists of presentation- and discussion sessions, complemented by written exercises and practical computer classes, where you are coached to process state-of-the-art radio interferometry data. The course covers the whole spectrum from Mega-Hertz to sub-millimetre radiation and from the cosmic dawn to galactic star formation, focusing on how to interpret data with different frequency- and spatial resolution.\n\nIn particular, the following aspects are covered:\n\nDetection of radio waves, telescope and receiver characteristics\nThe workings of interferometers and their response\nData processing techniques, such as image deconvolution and self-calibration\nThe AGN phenomena and the brightest radio sources\nRadio properties of the cold and warm interstellar medium\nSpecial radio sources, such as pulsars and masers\nDesign and data flow characteristics for interferometers like LOFAR, VLBI, ALMA, SKA\nSpectral line observation of molecules and HI throughout the universe\n\nOutcome:\nAfter this course you are ready to engage in scientific discussions that concern radio observations of astrophysical phenomena. You can compare how various radio telescopes and observing modes can be used optimally to investigate the astrophysical processes that generate long wavelength emission.\n\nAfter this course you can:\n\nWrite a clear, concise report describing a radio-interferometric data reduction and subsequent image analysis;\nDevelop a data reduction process from raw radio interferometric data to science-quality images;\nWrite an observing proposal for an appropriate radio telescope to answer a scientific question;\nAnalyse quantitatively how radio interferometric concepts affect a specific scientific result;\nExplain if and why certain radio image features are astrophysical or not;\nAnalyse to what extent signals are mutually coherent;\nIdentify common radio-astronomical data visualizations with their axis labels removed;\nIdentify the type of astrophysical object visualized in a figure;\nPerform basic Fourier-analyses, such as deriving a SINC function andqualitatively predicting the telescope’s response to a small collection of elementary shapes;\nDescribe (the function of) common components involved in a telescope’s signal processing;" . . "Presential"@en . "TRUE" . . "High contrast Imaging"@en . . "3" . "In this course you will learn how we detect faint structures next to bright stars, from exoplanets to circumstellar disks. The noise level in high contrast imaging is not set by the sky background but by the effects of diffraction in the telescope and science camera, summarised in a contrast curve that shows detection sensitivity as a function of angular separation from the central star. The relative contributions and characteristics of these noise sources are presented and discussed. We cover diffraction, quasi-static speckles and their time evolution, and the most recent developments in coronagraphs, and algorithms such as ADI, SDI, PDI, LOCI and PCA.\n\nThe course consists of a series of weekly lectures followed by a computer practicum class. The completion of the practicums will be part of the homework. There will be a take home exam at the end of the semester that will form part of the final grade.\n\nIn the course we cover:\n\nAstronomical sources of interest – exoplanets and exodisks\nA brief history of high contrast imaging\nThe Point Spread Function and its changes due to the atmosphere\nPoint source signal to noise and the contrast curve\nCoronagraphs: Lyot, band limited, pupil plane, focal plane\nAngular Differential Imaging, Spectral Differential Imaging\nDiversity and Algorithms: LOCI, PCA, optimized PCA\n\nOutcome:\nYou will gain an understanding of how to plan and take high contrast imaging data, how to interpret the attained sensitivity by generating contrast curves, and understand how several different algorithms are used and implemented to increase the sensitivity for faint point and extended sources.\r\n\r\nAfter completing this course, you will be able to:\r\n\r\nIdentify the data reduction techniques required to extract the astrophysical source\r\nWrite computer code and reuse code developed during the course\r\nDetermine the signal to noise of the resultant observations\r\nIdentify artifacts introduced by the algorithms and determine astrophysical signals" . . "Presential"@en . "TRUE" . . "Planetary physics: science and instrumentation"@en . . "3" . "Planetary science is now in its “Golden Age”. Dozens of spacecrafts developed and operated by ESA, NASA and other space agencies have delivered a wealth of valuable data about Solar System planets and exoplanets. Data analysis, theoretical studies and numerical modelling, aiming at understanding of the conditions and processes on the planets in the Solar System and beyond, especially those relevant to habitability, are in high demand. Future more sophisticated and challenging planetary missions are being planned and developed by space agencies.\n\nThis course will provide an overview of the methods and instrumentation currently used in planetary research supported by representative examples from recent Solar System missions. The course will deliver a broad picture of conditions and processes on the Solar System planets in their complexity and diversity. The students will also get a preliminary understanding of how concepts of planetary missions payload are designed, including setting up science objectives and requirements, defining priorities and complementarities. The course will provide a “bridge” to exoplanet investigations where appropriate.\n\nThe detailed outline of the course is:\n\nRemote sensing methods and instrumentation\nMethods and instruments for in-situ investigations\nGrand Tour of planetary surfaces\nGrand Tour of planetary atmospheres\nScience payload concepts: from objectives to requirements\n\nOutcome:\nUpon completion of this course, students will be able to:\n\nUnderstand the areas of applicability of various remote sensing and in-situ methods in planetary physics, their main features, advantages, limitations and main results\nAcquire a broad picture of main features and conditions on the planets in the Solar System\nDiscuss and explain major open questions in the planetary physics\nUnderstand and discuss the logics and the way science payload concepts for ESA planetary missions are being designed\nDiscuss and follow current literature in the field of planetary physics" . . "Presential"@en . "FALSE" . . "Active galactic nuclei (agn's)"@en . . "3" . "Active Galactic Nuclei (AGN) are extremely energetic objects that reside in the centres of galaxies. Often they are so luminous that they outshine their entire hosting galaxy. They can emit light over the entire electromagnetic spectrum enabling us to witness dramatic signatures of a wide variety of activities, ranging from radio jets that can be hundreds of times larger than galaxies to the observed heated accretion ring close to the black hole of our own galaxy. In this lecture series, AGN and their impact will be discussed in considerable detail.\n\nTopics that will be addressed include:\n\nobservational results and the resulting taxonomy\nthe physics of the various AGN building blocks\ntheir origin and time evolution\ntheir role in the formation of galaxies\n\nOutcome:\nUpon completion of this course, you will not only have a good understanding of the role AGN are playing in modern astrophysics but also have obtained a good feeling for the open questions in this field. The aim is to provide a solid background to be able to carry out research at the master or PhD level.\r\n\r\nUpon completion of this course, you will\r\n\r\nbe able to interpret observations at virtually the whole electromagnetic spectrum of AGN\r\nhave a good apprehension of how the basic physical properties of AGN building blocks are determined\r\nbe familiar with the various scenarios for the formation of the first AGN\r\nunderstand how AGN evolve and ideas on what might be driving this evolution\r\nbe acquainted with ideas on how AGN impact the formation of galaxies and methods that numerical simulations have employed to take this into account" . . "Presential"@en . "FALSE" . . "Galaxies: structure, dynamics and evolution"@en . . "6" . "In this course we will study the evolution of galaxies. Fundamental astronomical processes such as star formation, recycling and enrichment of gas, formation of planets, etc. all take place in galaxies. Besides that, galaxies are the basic building blocks of the universe, and we use them to trace the evolution of the universe. This broad scope is why galaxy research is in the forefront of astronomy.\r\n\r\nThis course covers the structure of the galaxies, including dark matter, stars and gas as well as the large scale structure in which galaxies are embedded. It discusses ongoing surveys of the nearby and distant universe. A special focus will be on the evolution of galaxies. The course builds on the bachelor course Galaxies and Cosmology and assumes that the material in this course is known to the student. A very brief recapitulation will be given of the most important material.\r\n\r\nCourse work consists of exercises, a presentation, and an oral exam. The presentation is on a paper or current research project; the oral exam focuses on the discussion of a research paper.\r\n\r\nTopics covered:\r\n\r\nTechniques how the mass distributions of galaxies are measured\r\nModeling the equilibrium of a gravitational system with a very large number of point sources\r\nStructure of nearby and distant galaxies\r\nObservational programs to study these galaxies\r\nObservations that have been used to understand the evolution of galaxies\r\nThe role of dark matter in galaxy evolution and formation\r\nAdvanced models for stellar populations and their application to the study of galaxy evolution\n\nOutcome:\nAt the end of this course, you:\r\n\r\nWill be able to analyze recent research papers in the general area of galaxy structure and evolution, and summarize their content and list their implications\r\nCan describe the structure and evolution of galaxies and can list the observables of galaxies underlying this knowledge\r\nCan explain the main mechanisms responsible for galaxy formation" . . "Presential"@en . "TRUE" . . "Astrochemistry"@en . . "3" . "The space between the stars is not empty but filled with a very dilute gas with extremely low densities and temperatures, providing a unique laboratory with conditions not normally encountered on Earth. A surprisingly rich chemistry occurs in these so-called interstellar clouds, as evidenced by the discovery of more than 200 different molecules. Some of these species were found in space before they were identified in a laboratory on Earth. How are these molecules formed? Where are they found and how do astronomers identify them? How do their abundances differ from place to place and what does this tell us about the structure of the region? How do the abundances evolve from cold clouds to planet-forming disks, where they can form the basis for prebiotic species?\n\nThe outline of the course is as follows:\n\nBasic principles of gas-phase and gas-grain chemical reactions\nChemistry in the early Universe\nChemistry in diffuse and translucent clouds, and in photon-dominated regions\nChemistry in shocks\nEvolution of molecular abundances from dark pre-stellar cores to star-forming regions\nChemistry in protoplanetary disks and links with comets\n\nOutcome:\nThe student will gain relevant background information that will enable him/her to follow the current literature on Astrochemistry and to do research in this field. The student will also acquire hands-on experience with running molecular excitation and chemical network codes, and make predictions for ALMA." . . "Presential"@en . "TRUE" . . "Astronomical spectroscopy"@en . . "3" . "Astronomical observation is a subject combining astronomy, quantum mechanics, and experimental spectroscopy. To accurately interpret and optimize the knowledge and societal impact of the obtained telescope data in various spectral ranges, it is crucial to have a rigorous understanding of the principles of theoretical and laboratory works.\r\nIn this course, you will learn to understand and apply atomic and molecular spectroscopy in an astronomical context. The course covers the basics of absorption spectroscopy and the history of astronomical spectroscopy. You will learn how to interpret spectra and what is needed to simulate molecular spectra for electronic, vibrational, and rotational transitions. The course highlights the synergy between observational and laboratory spectroscopy in astronomical research.\r\nThis course starts with general principles of quantum mechanics, and from these derives the principles behind atomic and molecular spectroscopy of molecules commonly found in the interstellar medium. You will apply the newly learned theory to the spectral simulation using the Pgopher software and compare them with observational data. Finally, general laboratory spectroscopy will be introduced to demonstrate how a typical molecular spectrum is measured in fully controlled experimental conditions.\n\nOutcome:\nUpon completion of this course, you will be able to:\r\n1. Read spectroscopic notation, and interpret and simulate (interstellar) spectra\r\n2. Explain the origin of atomic and molecular spectra\r\n3. Reproduce and simulate the typical shape of molecular spectra\r\n4. Calculate/explain physical parameters from spectra\r\n5. Read and summarize the literature on spectroscopy with astronomical applications\r\n6. Explain solid state and gas phase spectra obtained in the laboratory" . . "Presential"@en . "FALSE" . . "Observational molecular astronomy in galaxies"@en . . "3" . "Molecules pervade the cooler, denser parts of the Universe, in particular the reservoirs of the matter than forms stars and planets, and the gas in the centres of galaxies. These denser, cooler components of cosmic gas contain a significant fraction of the non-stellar baryonic matter in a galaxy and astronomers routinely use molecules to discover and explore these regions: the more complex the chemistry, the more details of the gas the molecules reveal. Hence, molecular line emissions offer astronomers exciting opportunities to learn how galaxies form, evolve and interact with each other.\n\r\nThe course will cover:\r\n\r\nA brief overview of what drives cosmic chemistry in different types of galaxies\r\nHands-on lectures on how to obtain useful astronomical information from raw telescope data\r\nDetermination of the suitable molecular tracers for many types of astronomical regions including starburst galaxies, AGNs, dwarf galaxies and high redshift galaxies.\n\nOutcome: Not Provided" . . "Presential"@en . "FALSE" . . "Exo-planets a: interiors and atmospheres"@en . . "3" . "We are in a unique time to study planets. Not only do we have space missions such as Cassini and Juno, which have led to a radical change in our knowledge of the giants in our solar system, but we also have an astonishing number of more than 4000 exoplanets that have been discovered in the last three decades. Each new exoplanet highlights a stunning diversity and impacts the perception and understanding of our own solar system. This course will provide an overview of our current theoretical understanding of the physical and chemical processes that occur in planets interiors and their atmospheres. This understanding is crucial to interpret observations, and to know where the field is moving for the developing of future instrumentation.\r\n\r\nThe detailed outline is:\r\n\r\nRadiative transfer in (exo)planet atmospheres\r\nChemistry in (exo)planet atmospheres\r\nPrinciples of fluid dynamics and applications to circulation in atmospheres\r\nInteraction between the planets and the host star: atmospheric escape\r\nInteriors or rocky planets\r\nInteriors of giant planets: inflation in hot-Jupiters\r\nInteractions between interiors and atmospheres: surface, ocean and volcanoes\r\nThe concept of habitability\n\nOutcome:\nUpon completion of this course, you will be able to:\r\n\r\nDistinguish the main physical and chemical processes that shape the atmospheres and interiors of (exo)planets.\r\nDiscuss and follow current literature in exoplanets\r\nUse state-of-the-art codes to model exoplanets interiors and atmospheres\r\nName the main uncertainties in the current knowledge of Exoplanet interiors and atmospheres\r\nIdentify synergies between our Solar system and Exoplanets" . . "Presential"@en . "FALSE" . . "Exo-planets b: space physics"@en . . "3" . "The emphasis of Part B of the Exoplanets course is on the “exterior” of planets, namely, from the upper atmosphere and beyond. Planets do not exist in empty space, but they are rather embedded in the particle, magnetic and radiation environments of their host stars. As a consequence, the interaction between planets and their host stars leads to escape of planetary atmospheres, shapes (and sometimes induces) planetary magnetospheres, and affects the space weather on a planet.\n\nThis course focuses on Space Physics, and covers the following topics:\n\nPlanetary upper atmospheres: atmospheric escape (thermal vs non-thermal); Jeans escape; hydrodynamic escape and energy-limit approximation; primary and secondary atmospheres; detection of escaping atmospheres in exoplanets\nPlanetary magnetospheres: magnetism in solar system planets, intrinsic magnetosphere, induced magnetosphere, magnetopause distance, ionopause, magnetic fields in exoplanets.\nSolar and stellar activity: spot cycle, flares, magnetism and proxies for magnetic activity; effects of stellar activity on exoplanet detection.\nThe interplanetary medium — solar and stellar winds: basic concepts of fluid dynamics, overview of stellar winds over the HR diagram, forces driving a stellar wind, thermally-driven winds, winds of a magnetic rotator, Alfven surface, mass- and angular-momentum losses, evolution of stellar rotation.\nSpace weather: origin, impacts, events and mitigation.\n\nOutcome:\nOn successful completion of this course, students should be able to:\n\nDerive the equations responsible for the stability of planetary atmospheres and magnetospheres\nExplain the key processes responsible for solar and stellar activity and their space weather effects on (exo)planets\nExplain the physics of winds of planet-hosting stars; derive the basic wind equations and evaluate the wind forcing on (exo)planets" . . "Presential"@en . "FALSE" . . "Observational cosmology"@en . . "3" . "The purpose of this course is to provide a general overview of the observational basis for our modern view of cosmology. Topics that will be covered include:\r\n\r\nMajor tests used to establish the age of the universe\r\nHubble constant\r\nDark matter\r\nDark energy\r\nBaryonic content of the universe\r\nMatter power spectrum\r\nThe ‘w’ parameter\n\nOutcome: Not Provided" . . "Presential"@en . "TRUE" . . "Science methodology (scm)"@en . . "4" . "During the BSc and MSc education, students learn lots of scientific facts, but do they know how science works? In this course the basic principles of the methodology used in the natural sciences are taught. The aim is to let the student contemplate on concepts like ‘truth’, ‘experiments’, ‘models’, ‘confirmation/falsification’ and make the student aware of the limitations of the ability to make objective observations. Also current practices, like the mechanisms of research funding, ‘publish or perish’ dogma and the importance of impact as well as integrity and ethics in science will be discussed.\n\nOutcome:\nAt the end of the course students:\r\n\r\nhave a basic knowledge of the philosophy of science\r\nhave a basic understanding of modern scientific practices\r\ncan critically discuss aspects of the scientific enterprise orally as well as in writing\r\ncan critically discuss the relation of science and society orally as well as in writing" . . "Presential"@en . "FALSE" . . "Science and the public: contemporary and historical perspectives"@en . . "6" . "Science has often been held to exemplify the values which operate in the public sphere in an open society. It has been treated as a model for the democratic discourse through which the state is held accountable in public. Yet, science as specialized expertise, fostered in elite communities, is also detached from the lay discourse of the public sphere. This detachment is increasingly challenged as skeptical publics question expert prerogatives. This course aims to offer a careful understanding of the interrelationship between science and the public. Students will learn about different aspects involved in the way scientists, intermediaries and institutions have interacted with the public sphere in the past and continue to do so. Topics that will be addressed are the popularization of science, public (dis)trust in science, scientific expertise and public law, classified science and secrecy, the depiction of science in the media, science museums, and science based government campaigns aimed at the general public. In this course, we will discuss critical texts on these topics after a brief introduction by one of the students. Excursions to museums are also included. A final essay will conclude the course.\n\nOutcome: Not Provided" . . "Presential"@en . "FALSE" . . "First project: research"@en . . "27" . "Astronomy master's students in the specialisations Astronomy Research, Astronomy and Cosmology, Astronomy and Data Science or Astronomy and Instrumentation carry out two astronomy research projects: the First Research Project and the Master’s Research Project. The First and Master's Research Projects must be on different topics. Students in the Astronomy and Business Studies (BS), Astronomy and Science Communication and Society (SCS) or Astronomy and Education specialisations carry out only the Master’s Research Project.\r\n\r\nThe First Research Project is an important first step in your training as an Astronomy master's student at Leiden University. During a period covering at least half of the first year, your engage in state-of-the-art research, supervised by a Leiden Observatory scientific staff member. You are free to choose your research topic along the full spectrum of modern astrophysics. Projects may involve observations, theory, simulation and hands-on experimentation. During the First Research Project, you are hosted at Leiden Observatory; you will get a desk, a computer, and attend regular meetings within your research group. The First Research Project is concluded with a thesis.\n\nOutcome: Not Provided" . . "Presential"@en . "TRUE" . . "Master project: research"@en . . "27" . "The Master's Research Project is an integral and vital part of your training as an Astronomy master's student at Leiden University. During a period covering at least half of the second year, your engage in state-of-the-art research, supervised by a Leiden Observatory scientific staff member. You are free to choose your research topic along the full spectrum of modern astrophysics. Projects may involve observations, theory, simulation and hands-on experimentation. Keep in mind that if you do two projects, the First Research Project and the Master's Research Project must be on different topics. During the Master's Research Project, you are hosted at Leiden Observatory; you will get a desk, a computer, and attend regular meetings within your research group. The Master's Research Project is concluded with a Master's Thesis and a Student Colloquium.\n\nOutcome: Not Provided" . . "Presential"@en . "TRUE" . . "Astronomy student colloquium"@en . . "0" . "All Astronomy Master's Research Projects are concluded with a public presentation, referred to as a Student or MSc Colloquium. This presentation will be graded by the Student Colloquium coordinator for your presentation skills and not for the scientific content or the way you conducted your research. Prepare your talk well using these presenting tips and action plan for your presentation, and practice your talk well in advance within your research group. Immediately after your talk, you will receive feedback on your presentation and a pass/fail grade.\r\nNote: in the specialisations Astronomy and Business Studies, and, Astronomy and Science Communication and Society, the Student Colloquium can be given on either the Master's Research Project or on the internship or research project carried out for the BS/SCS component of the programme, with a preference for the former. Note that the Student Colloquium requirement is separate from any other presentations that may be required for these specialisations.\r\n\r\nAs an Astronomy master's student, you have to plan your own Student Colloquium, which will be held in the format of an Astronomy master's colloquium conference three times per year (October, January and June, as shown in your schedule). You will get the opportunity to register for a colloquium slot approximately two weeks before the start of each conference, via a link that will be sent to your @strw email address.\n\nOutcome: Not Provided" . . "Presential"@en . "TRUE" . . "Master of Astronomy and Data Science"@en . . "https://www.universiteitleiden.nl/en/education/study-programmes/master/astronomy/astronomy-and-data-science" . "120"^^ . "Presential"@en . "In the master’s specialisation Astronomy and Data Science you focus on development and application of new data-mining technologies, fully embracing modern astronomy as a data rich science. You combine the research curriculum in Astronomy with in-depth training in Computer Science.\n\nThe Astronomy and Data Science master’s programme is built on world-class computational astrophysics research as well as hightech industry expertise. It covers a wide range of research areas studying complex astronomical phenomena, including radiative transfer, computation of dynamical internal galaxy structures and hydrodynamical modeling of galaxy formation and evolution of the intergalactic medium.\n\nThis two-year Astronomy and Data Sicence programme uniquely combines advanced Astronomy courses of the Leiden Observatory and relevant courses from the Computer Science master’s programme of the Leiden Institute of Advanced Computer Science including advanced data mining and neural networks. To this end, the Leiden Observatory offers sophisticated computational facilities ranging from local computer clusters to high-performance systems at national and international computing centers.\n\nOutcome:\nDuring the programme, you learn to perform academically sound research and evaluate scientific information independently and critically. Without exception, you actively participate in current research within the institute and are individually supervised by our international scientific staff. Students with a Leiden degree in Astronomy become strong communicators and collaborators and can easily operate in an international setting. You will acquire extensive astronomical research experience and highly advanced analytical and problem solving skills."@en . . . . . . "2"@en . "FALSE" . . "Master"@en . "Thesis" . "2314.00" . "Euro"@en . "19600.00" . "Mandatory" . "Most graduates holding a MSc degree in Astronomy from Leiden University find work in many different capacities, including:\n\n1. Research: universities, observatories, research institutes\n2. Industry and consultancy: ICT, R&D, telecom, high technology, aerospace\n3. Finance: banking, insurance, pension funds\n4. Public sector: governments, policy makers, high schools\n5. Science communication: journalism, popular writing, museums\n6. Typical jobs for Astronomy graduates include:\n\nScientific researcher (postdoc, research fellow, professor)\n1. R&D engineer\n2. Consultant\n3. Data scientist, statistician\n4. Policy advisor, public information officer (e.g. Ministry of Foreign Affairs)\n5. High school physics teacher\n6. Scientific editor for magazines, newspapers and other media\n7. Research at Leiden Observatory\n\nIf you want to get more deeply involved in research after graduating in Astronomy, consider pursuing a PhD at Leiden Observatory. If you have completed the Leiden master’s degree programme in Astronomy, you are directly eligible for admission to our PhD programme"@en . "no data" . "TRUE" . "Upstream"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "Faculty of Sciences"@en . .