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Development, Schooler META Lab, Department of Psychological & Brain Sciences Job #JPF03136 Psychological and Brain Sciences / College of Letters & Science - Mathematical, Life, and Physical Sciences
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techniques to travelling-wave and spectral stability problems. Potential applications include mathematical biology, superconductivity and nonlinear optics. The position offers opportunities for
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date may also be considered if there are special grounds, for example, different types of statutory leave of absence. The research tasks require a solid mathematical background with proven advanced
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Stochastics and the Community of SURE-AI . The focus is on the development of original mathematical methods for AI and its applications aimed at the modelling and analysis of complex phenomena particularly
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and medical research questions. Strong expertise in (Bayesian) statistics and data science Experience with mathematical modelling (e.g., linear algebra, linear models methodologies) Demonstrated
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intelligence, image understanding, or related areas Proficiency in Python programming; solid understanding of computer science fundamentals Experience with version control (GitHub) and AI coding assistants (e.g
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looking for a PhD candidate to develop and evaluate a mathematical model and algorithm to better tailor (risk-based) follow-up after cancer treatment. The role is highly impactful for ensuring sustainable
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across laboratory experiments, mathematical modelling and commercial ripening facilities, you will investigate how mangoes respond to their environment, develop methods to monitor ripening in real time
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-informed reconstruction. Scientific track record with publications at internationally renowned venues in machine learning. Solid mathematical background, distinct analytical and numerical skills. Solid
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statistical/mathematical foundations relevant to modern data science (e.g., Bayesian or frequentist inference, information theory, uncertainty quantification, high-dimensional methods). Programming skills