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-informed / simulation-aware modeling Efficient algorithms for design-space exploration (e.g., surrogate modeling, Bayesian optimization, differentiable programming) Hybrid approaches combining data-driven
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programming languages such as R or Python Experience with multiome data analysis (e.g. methylomics, Lipidomics, Proteomics, ATAC-seq) Proven experience with advanced computational methods such as deep and
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and Python programming skills are an advantage. Passionate about science communication and cultivating collaborative relationships with industry professionals. Excellent written and spoken English. A
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available in the further tabs (e.g. “Application requirements”). Programme Description The Kurt Hansen Fellowship supports teachers, trainee teachers, and students of teaching subjects or pedagogy in the STEM
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Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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datasets Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl, C++, R) Well-developed collaborative skills We offer The successful candidates will
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. Strong quantitative skills (e.g., econometrics, optimization, I/O table, CGE, simulation modeling) and solid programming experience (e.g., Python/R/Matlab/C). Preferred (optional): familiarity with machine
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research program focused on developing next‑generation multimodal imaging systems spanning the mesoscopic to microscopic scale. As part of a major research project and supported by extensive national and
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Remuneration according to TV-L incl. occupational pension plan and capital-forming payments 30 days of vacation per year Flexible working hours Possibility of part-time work Family-friendly working environment
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opportunity to learn the process and challenges of drug discovery from the inside, including additional training and mentoring program. In addition, benefit from the rich packages for employee benefit. Our most