| source Universitetet i Oslo (X) |
level Ph.D. level course (X) |
department |
Provides an in-depth introduction to adaptive dynamics, a theoretical framework for studying frequency- and density-dependent evolution with a high degree of ecological realism. This framework integrates and extends concepts and techniques from evolutionary game theory, with special emphasis on dynamical phenomena such as the origin and divergence of new lineages by evolutionary branching.
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This course introduces students to the methods most commonly used in empirical finance. The analysis of different financial markets and instruments will be discussed, as well as how to handle different data frequencies (tic, hourly, daily, weekly, monthly data). Key models and methods: ARCH, GMM, Regime Switching. Prediction of risk and returns; test of CAPM (Capital Asset Pricing Model), stock market prices, derivatives (exchange rates, forwards, options, swaps), term structure models, volatility models (implied, stochastic volatility) elementary microstructure.
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The course deals with econometric modelling of the following phenomena:
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Panel data is a data type which is receiving gradually increasing interest for empirical analysis in economics. The course deals primarily with econometric modelling, estimation, and testing of relationships for panel data (combined cross section/time series data) in the presence of individual heterogeneity. Selected topics in time series analysis, especially topics of relevance for panel data analysis of dynamic models, will also be discussed.
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The course deals with econometric modelling, estimation, and testing of relationships and models for time series data with main focus on methods for handling non-stationary time series.
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Dynamic optimization, both deterministic and stochastic.
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General topics in mathematics. The topics of the course will be discussed with the participants at the beginning of the course.
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To develop a basic understanding of stochastic processes useful in economic research. The aim is also to develop a basic skill in modelling economic phenomena characterized by stochastic dynamics, and an ability to analyse such models. A textbook and a compendium will be used for presenting theory, and several papers will be used to study particular models and analyses.
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The first part of the course provides a formal understanding of game-theoretic solution concepts. It seeks to give the participants a critical attitude when applying such concepts in economic applications. The second part of the course provides similarly an understanding of basic information problems (such as hidden action, hidden knowledge, non-verifiable information) and how they can be partly solved through contract design. It seeks to enable the participants to apply the theoretical tools developed in contract theory in economic applications.
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The course overview may change according to the interests of the students.
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This course is designed to develop a working toolbox for Ph.D. students who would like to conduct research in applied theory. The course teaches basic tools of modern macroeconomics, which has direct applications to a broad set of fields in economics (labor economics, political economy, development, asset pricing, and others). The ultimate goal of this course is to learn to use a variety of models that can be used to give quantitative answers to a number of economic questions.
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This course is designed for science based students with an interest in innovation. Focus is on industry dynamics of science based innovations, and on the formulation and implementation of innovation strategies. The course highlights the advantages and disadvantages of intellectual property rights in relationship to the development and trade of an innovation. The course also addresses how to formulate the criteria for the most frequently used rights.
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The course is dealing with aspects of glycoconjugates both from a biological and structural point of view. Both mammalian and plant glycopolymers will be dealt with. The focus is on compounds that have a possible use in pharmacy and medicine especially against illnesses and injuries that may involve the immune system. Details related to structure- activity relationships will be in focus, also methods used for studying these aspects. Localization and function of the polymers in nature will also be discussed.
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Quantum formalism; path integrals and coherent states. Quantum mechanics and probability, entanglement and EPR paradox. Quantum physics and information, bits and qubits. Atoms and photons, photon emission and absorption, coherent states of light. Laser. Adiabatic evolution and geometric phases. Macroscopic quantum states, quantum physics in low dimensions.
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Gell-Mann-Low theorem. OS-renormalization. Cut-off and dimensional regularization. IR- and UV-divergences. Renormalization of QED, Bloch-Norsieck-result, vacuum-polarization and effective charge. Path integral and functional methods, correlators and generating functionals. Euclidean and finite T-field theory. Grassmann-variables and integration. Renormalization group, MS-renormalization, Callan-Symanzik-equation, beta-function and anomal dimensions. Effective theories. Non-abelean gauge theories, generalized Lorentz-gauge. Faddeev-Popov determinant. Asymptotic freedom and QCD. Electroweak theory, Higgs-mechanism and equivalence theorem.
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Einstein-Hilbert action and quantum fields in curved spacetimes. Inflation and reheating. Quantum fields at finite temperature. Standard model in the early universe. The Boltzmann equation. Cosmological phase transitions. Baryogenesis. Nucleosynthesis and recombination. Microwave background radiation. Quantum fluctuations and the primordial spectrum. Cosmological pertubation theory.
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Quantisation of free scalar, vector and Dirac fields. C-, P-, and T-symmetry. Lorentz symmetry. Noethers theorem. Interacting fields for quantum electrodynamics (QED). Generalisation to non-abelian theories for electroweak and strong interactions. Derivation of Feynman rules. Elements of renormalisation.
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Elements from modern computer architecture, input/output units, microprocessor buses. Instrumentation systems, signal transmission and signal transformation, operating systems for real time, real time activities, parallel activities, synchronising, communication, resource distribution, programming language for real time applications, data structures, signal processing, reliability, operator communication, graphics, practical system development, simulation of data collecting systems.
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Microsystems are small sensors and actuators that can be connected by electronics in small systems. Microsystems are very important in areas like medicine, biotechnology, communication and security. Microsystems is an area of commitment in Norway.
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Medical terminology. General diagnostics. Electrophysical methods like ECG, EEG, EMG, defibrillator and pacemaker. Measurement techniques for respiration and circulation. Methods for intensive monitoring. clinical/chemical measurement techniques. Disinfection/sterilisation, sensors. Imaging techniques: X-rays, nuclear medicine, ultrasound, magnetic resonance. Supporting instrumentation like incubator, respirator, anaesthesia machine and dialysis machine. Surgical techniques with diathermy and laser.
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Design, production and properties of different components used in electronic products. Component encapsulating. Circuit boards and other component carriers. Production processes for electronics. Soldering, bonding and gluing. Hole mounting and surface mounting. Thick/thin film hybrid technique, polymer thick film technology, "Chip-on-board", TAB, automation, flexible robots. Reliability.
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The preparation and processing of semiconducting in the making of modern nano-electronic devices and test structures for research is used as a framework and covers topics from crystal growth to ridiculously large scaled chips. General principles and examples from Si, Si-Ge and III-V technology: Crystal defects; van Vechten's vacancy model, Fair's diffusion model, stacking faults and dynamics, pair production in doping, deep levels, gettering, interaction between low-energy particles and semiconducting materials, interaction plasmas with surfaces. Experimental techniques for characterising semiconductor structures : AES, RBS, TEM, SEM, SIMS, ellipsometry, FTIR, DLTS etc. Description of semiconductor processing: epitaxial crystal growth, MBE, MOCVD, diffusion ion implantation, ion etching, oxidation, thin-film technology, silicide production, laser processing, lithography. Process integration of example technologies CMOS and MEMS.
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Theory of elastic and inelastic scattering of electrons. Dynamic scattering theory: Bloch-wave and multi-slice theory. Absorption and diffuse scattering. Electron channelling: Emission of secondary radiation and ALCHEMI. High resolution electron microscopy (HREM), convergent beam electron diffraction (CBED), energy dispersive X-ray spectroscopy (EDS), electron energy taps spectroscopy (EELS), electron holography. Applications of electron diffraction, electron microscopy, and spectroscopy in structure research. Determination of crystal and electron structure.
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Contents: Diffraction methods and their applications to structure problems, in particular to alloy systems and other inorganic materials. Crystallography. Diffraction from lattice defects. Imaging and contrast in electron microscopy. Kinematic and elementary dynamical theory of electron diffraction. Interpretation of contrast from defects. The transmission electron microscope and its principles. Briefly about other electron beam instruments.
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Techniques for controlling experimental setups, dynamic light scattering, neutron scattering, image processing techniques. The course is based on different projects where the students apply the techniques on realistic problems from condensed matter physics.
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