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Max Planck Institute for Biological Cybernetics, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 6 hours ago
and fUSI studies, including data analysis (e.g., Afni, Matlab, Python), MRI physics & sequence development, rodent handling, behavioral experiments and surgery. Our mission is to build a supportive and
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, machine learning (PINN, supervised learning) - Python/PyTorch programming - Autonomy, curiosity, and adaptability - Excellent writing skills Specific Requirements The doctoral student's host laboratory is
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experience with finite element or finite difference modelling and its underlying fundamentals. The student should be able to program in MATALB or Python (MATLAB preferred as lead supervisor is more familiar
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/Computer Engineering, Computer Science, Applied Maths or related. Strong skills in AI techniques/ML/optimisation (Python/Matlab); familiarity with probabilistic modelling, time-series or control/power
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Experience and practical knowledge of programming languages and tools (e.g. Python, Java, etc.) Knowledge in Software Engineering, AI, machine learning is an advantage Experience with software observability
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culture and in vitro models of mucosal immunity Data analysis using Python and digital image processing These skills are highly transferable to careers in biomedical research, pharmaceutical development
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topics and debates in ecology • Experience with a programming language (e.g., R or Python) and data analysis • Sound knowledge of English and the ability to write scientific publications
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, particularly insect decline and species distribution models (SDMs), are desirable • Experience with and knowledge of a programming language commonly used in data science (e.g., R or Python) • Experience and
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or Python) • Good knowledge of the English language • Experience with statistics, machine learning, Deep Learning and AI are an advantage • Familiarity with fundamental ecological concepts and experience in
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. Desirable Skills (an advantage, not a requirement) Data analysis skills in python. An interest in energy policy / the economics of energy. Numerical modelling. Eligibility This studentship is available for UK