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, ideally with experience in generative models, reinforcement learning, or high-dimensional optimization. Programming proficiency in languages such as Python. Ability to work both independently and in a team
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the Python programming language is an absolute requirement Experience with global vegetation models, satellite products (L3 or L4), and/or machine learning applied to spatially explicit data would be an asset
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policy, economics, statistics, or a related quantitative field Additional Qualifications Strong skills in Stata, R and/or Python and experience analyzing complex data Demonstrated experience working with
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, Python, and SAS or Stata Demonstrated expertise in analysis of claims data Clear scientific writing and communication, an ability to work both independently and in teams, and a track record of publications
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demonstrated proficiency in programming, specifically in Python and R, as well as experience with modern deep learning frameworks like PyTorch or TensorFlow. In addition to technical skills, the candidate must
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quality assurance Furthermore, collaboration with experimental and other theoretical groups in Vienna is desirable. Candidates should also actively contribute to and collaborate with the CRC TACO, https
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, natural science, quantitative science or in related fields affinity to programming, including programming in MATLAB, Python, or similar advanced English communication skills strong analytical skills strong
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good collaborative skills It is an advantage with experience performing experiments on fish or other animals. strong quantitative and data-handling skills (e.g. using R/python or an equivalent
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analysis. Background in statistical or physical models of proteins (e.g., Potts models, energy landscapes, coevolution). Strong background in biophysics. Programming skills in Python, R, C++. Experience
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robustness, fairness, and accessibility. You will design and run reproducible experiments, measure relevant resource metrics, implement prototypes in Python, and communicate results through publications and