Sweden

Antibiotics were once regarded as miracle drugs. However, they are becoming less effective as bacteria develop resistance against them. The increasing occurrence of micro-organisms that are resistant to multiple antibiotics constitutes a serious threat to human health. The course addresses fundamental questions and problems concerning antibiotics such as what is the role of antibiotics in nature? How are they synthesized? What are their modes of action? How can new antibiotics be discovered? How can we attack problems with antibiotic-resistant microorganisms? The course brings a comprehensive understanding of the biology and chemistry of antibiotics. It provides insight into bacterial physiology and also industrial and clinical aspects of antibiotics and the evolution of antibiotic resistance.

The development of suitable models for describing dynamical systems is a central problem within automatic control, and it is critical for the development of robust and high-performance control laws. When relationships between physical quantities are not fully known, then models and the control laws may instead be generated by measurement data, through system identification, machine learning, or adaptive control. The purpose of the course is to teach the basic principles of how this is done. The first part of the course is devoted to adaptive control and system identification for systems with several input and output signals. The focus is on state-space models and methods for generating these, including grey-box identification. The course describes iterative methods for learning, as well as model reduction for the purpose of reducing the dimension of the state space. The second part of the course is devoted to reinforcement learning. This includes the theory of dynamic programming and various approximate methods thereof. Policy iteration is explained, as well as discrete and continuous path planning. The third part of the course deals with the usage of complete components for the purpose of control, for instance, sensors that have been developed using machine learning.

The course gives an insight into how functional programming often offers a possibility to write shorter and easier-to-understand programs than using the traditional imperative or object-oriented approaches. Course content includes the philosophy of functional languages, the programming language Haskell, language constructs and idioms, higher-order functions, lazy evaluation and infinite data structures, monads and monadic computations polymorphic type systems and type classes, and type analysis and type inference.

The course is intended to introduce some basic formal concepts and terminology pervading all areas of computer science, and to establish a common lexicon, including notational conventions and nomenclature, that subsequent courses can build upon. This includes an introduction to abstract set theory, relations, functions, ordered sets, Boolean algebra, logic, and proof techniques, as well as structures such as graphs and trees. Furthermore, the course discusses basic algorithms on graphs, an introduction to combinatorics, some fundamental proof strategies, and basic order structures such as lattices and complete partial orders (CPOs).

 

This course provides methodologies and tools for the adaptation of water resource systems with respect to climate change and climate variability. The course provides a fundamental understanding of the physical processes behind climate change and its effects on the hydrological cycle.  Course topics include the climate of the world, global circulation patterns, climate variability, basic meteorology, rain-generating processes, downscaling in time and space, changes in rainfall patterns, extreme events, disaster risk reduction, sea level change and its consequences on near-shore constructions, urban hydrology, maintaining quality drinking water in a changing climate, and problems unique to arid areas and developing countries.

The course examines the significance of cultural heritage and cultural memory in the United States in historical and contemporary perspectives. It centers on questions about identity, nationalism, politics, and commercialism, how history has been represented in for example monuments, museums, commemorations, political debates, and popular culture, as well as the conflicts that regularly occur in the United States around questions of cultural memory and heritage.

The course covers hydrogen as an energy carrier, how to produce it, and how to store it. The role of hydrogen in future energy systems is discussed. Electrochemical conversion in batteries and fuel cells is described and analyzed. All major transport processes, such as momentum, heat, mass, ion and current, and thermal management issues are presented. System integration is described. Properties and characteristics of energy-relevant materials and their role in electrochemical devices are treated. The relevance of energy systems and the transportation sector is discussed. Various engineering problems are presented.

This course discusses similarities of concepts and methods in finance and physics in order to enhance cross-fertilization of these fields. The course contains portfolio theory and constrained optimization, relations between stochastic differential equations, regression models, time series and forecasting. Bubbles, crashes, and path integrals in physics and finance is also part of the course.

This course examines morphology and syntax in English texts from two time periods. While inflections played an important role in Old English grammar, present-day English relies primarily on structures where word order and function words are of central importance. Students thus investigate morphological and syntactic aspects of Old and present-day English texts. Through independent research projects, students also learn how to apply methods of morphosyntactic analysis to authentic texts in order to describe the structure of English.

The course introduces computational approaches to model human behavior and social phenomena. Core concepts in computational social science are covered, such as observational studies (what types of data exist, possible biases, and how to use data for modeling), basic concepts and techniques for running experiments (asking vs. observing, natural experiments, simulations, validity, and generalization) and discuss key issues such as ethical considerations. The course has both a theoretical and a practical perspective, where you learn basic principles and also how to apply them in practice in three main areas: social network analysis; text analysis; agent-based modeling, and simulation.