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science, geoscience, physics, engineering or a related discipline. Experience with quantitative data analysis and scientific programming, preferably in Python is required. Experience with
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: Outstanding scientific programming skills (Python, PyTorch/JAX) with a proven track record of developing, debugging, and scaling complex RL pipelines or custom simulation environments. Clean public
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-stationary environments. Implementation Expertise: Outstanding scientific programming skills (Python, PyTorch/JAX) with a proven track record of developing, debugging, and scaling deep generative
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background in thermodynamics, transport phenomena, and process modelling and computer programming with documented experience in developing and applying unit operation and flowsheet models for chemical
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species distribution models, joint/hierarchical community models, dynamic vegetation models, or related biodiversity forecasting approaches; advanced programming skills in R and/or Python and
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communication skills Experience with all-atom and/or coarse-grained molecular simulations Programming skills and experience working in a Linux environment Candidates with backgrounds in: Physics Physical
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Postdoctoral position in biomolecular simulations of membranes and membrane proteins at SDU in Od...
coarse-grained molecular simulations Programming skills and experience working in a Linux environment. Candidates with backgrounds in: Physics Physical Chemistry Engineering are particularly encouraged to
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Policies and their architectures - Advanced programming skills What we offer - a well-developed research infrastructure, laboratories and access to shared equipment - an exciting interdisciplinary
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Experience with programming in Python, R, or similar languages Background in machine learning or deep learning methods Knowledge of genomics, transcriptomics, evolutionary biology, and plant biology is an
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programming in Python, R, or similar languages Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to