Bioengineering

The course covers the biomechanics and mechanobiology of skeletal tissues (bone, articular cartilage, tendons, and ligaments); the pathomechanics of injury, adaption, and degenerative changes with aging; how biomaterials can be used in loaded regions of the body; and an insight into current biomechanical research of skeletal tissues.

This course provides a theoretical introduction to microscopy, with an emphasis on fluorescence microscopy. Topics include theoretical principles of confocal microscopy and the use of deconvolution in microscopy, an overview of different types of advanced research microscopes as well as imaging methods that are not based on optical microscopes; preparation and optimization of both fixed and live samples for microscopy; microscopic visualization of cellular structures and physiological functions with fluorescent markers; and a theoretical introduction to digital visualization, with an emphasis on fluorescence-based methods and digital imaging. A practical project includes the preparation, documentation, and analysis of microscopy specimens with an oral and written presentation.

The course provides students with a fundamental grounding in the theoretical and computational skills required to apply machine learning tools to real-world problems. It will provide an understanding of the application of these skills to explore complex high-dimensional data sets; providing an overview of active research areas in machine learning, with biomedical applications.

This course provides the foundation of modern food microbiology by using relevant examples from the food industry. The course covers the following themes: growth and survival of microorganisms in foods, preservation, food spoilage, food pathogens, fermented foods, genetically modified organisms, and rapid detection methods.

This course provides a foundation in understanding and solving problems related to biomedical engineering applications of momentum, heat, and mass transport phenomena. Students are expected to have completed coursework in calculus and physics. Previous coursework in differential equations, fluid biomechanics, and numerical methods is recommended.

This course provides a study of continuous and discrete-time signals and LTI (linear and time-invariant) systems in the time and frequency domain. Topics covered include: signals; systems; Fourier series representation of continuous-time periodic signals and sequences; continuous-time Fourier transform; sampling; Laplace transform and z-transform. Students are expected to have completed coursework in calculus and linear algebra.