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data science, biomedical engineering, technical medicine, or a related field. You should have strong programming skills (Python, PyTorch), deep learning knowledge (multimodal learning, longitudinal
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, or related methods, is also advantageous. Programming and data analysis skills in Python, MATLAB, R, or similar are advantageous. Proficiency in English; German is a plus. Enthusiasm for interdisciplinary
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skills. experience in data analysis, quantitative modeling and programming (e.g., R, python); knowledge of nutrient and/or agrochemical cycles in agriculture; excellent scientific writing skills in English
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desirable: microwave engineering, confocal microscopy, scanning probe microscopy, magnetic resonance spectroscopy, and scientific programming in Python. Prior experience with hardware electronics such as
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experts on dynamical systems and ergodic theory, postdoctoral researchers Josias Reppekus and Misha Hlushchanka, both active in different areas of complex dynamical systems. PhD students and postdoctoral
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perception, optimization, or control will be an advantage. The candidate should be comfortable with scientific programming, for example in Python and common machine-learning frameworks such as PyTorch
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related field; a solid understanding of molecular genetics, glial and myelin biology and rare neurological diseases; experience with either iPSC culture and differentiation or programming (Python and/or R
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research. The ideal candidate will have a strong foundation in Python programming and hands-on experience with deep learning frameworks such as TensorFlow or PyTorch. Applicants with a background in Natural
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mathematics. Strong programming skills in Python. Ideally, also proficiency in at least one major deep learning framework (e.g., PyTorch, JAX). An early track record of research (e.g., a high-quality Master's
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. Fluent oral and written communication skills in English. Desirable qualifications Documented Experience with Python and/or another scientific programming language. Documented Experience with image