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Field
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performing data analysis of B cell receptor repertoire data using programming languages (mostly R) Successful candidates can think independently, are eager to acquire necessary new skills, and are excellent
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an extended period of time. The research classes are based upon the cooperative work of the group and the principle of peer learning. In addition, both faculties offer numerous colloquia that cover key areas
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, which facilitate their daily life outside the lab. Students attend seminars, journal clubs, lectures, and conferences. They learn to present their data to their peers, including those who work in an area
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. It begins with an orientation year where students can choose up to three laboratories of the fellows to acquire interdisciplinary perspectives on common research themes in the area of Cognition. In
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of potentially novel modes of protein binding is possible in collaboration with other members of the lab. Desired (but not absolutely required) skills: programming in python, machine learning, and experience in
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performance in fuel cell (biogas) and co-electrolysis applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under
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mostly provides an evaluation of the student's general astronomy background and should indicate where further learning is desirable. The IMPRS Advanced Courses consist of seven one-week morning lectures
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applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under various operating conditions and develop strategies
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: doi.org/10.1002/advs.202409386 Your Tasks Defining security. You define security requirements for physical one-way functions Security analysis. You test non-invertibility using machine learning attacks
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-harvesting complexes. The research will use a combination of quantum and molecular dynamics simulations, electronic structure calculations, and machine learning approaches. These are similar to earlier work