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, parameterization, simulation experiments, and output analysis very good programming skills in at least one language (e. g., R, Python, C++, or Julia) a strong interest in interdisciplinary work (e. g., demonstrated
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. Programming experience is required (Python, R). Strong analytical, organizational, and record-keeping skills Interest in working in a multidisciplinary and multicultural team Willing to collaborate with
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programming or scripting (e.g., Python, Bash, or similar) for workflow automation and data analysis. Familiarity with common tools for structure-based molecular modeling or virtual Ability to think critically
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setups and instrumentation, in particular in-situ computer tomography Proficiency in one or more programming languages relevant to the task (e.g., Python, Matlab, LabVIEW, C++) Experience in programming
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, TensorFlow, Pandas), ideally combined with knowledge of data visualization or statistical analysis Knowledge of software development (e.g., Python, Matlab, Simapro), especially in combination with experience
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, computational data analysis and microbial evolution, with a solid understanding of quantitative statistics and programming (Python, R, MATLAB, etc.). Additional expertise in ancient DNA, (bio)archaeology
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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, cloning etc.) Preferably knowledge in the characterization of microbial rhodopsins Skills in data analysis with Python Excellent organizational, interpersonal and communication skills The ability to work in
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, Genetics, Cell Biology, Biophysics or a related field - Competency in computational (R or Python) and statistical analysis - Competency in experimental design and standard molecular biology, imaging
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, biomedical engineering, or a related field. • Experience with coding software such as Python, R, or Matlab. • Familiarity with collaborative coding software such as GitHub and database management