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and solids. Experience in scientific programming in C/C++, Python, Fortran, Mathematica or similar is required. The successful candidate will either hold a PhD in Physics or a related area, or
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g
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career scientist with PhD(or equivalent) in Plant Biology, Biochemistry, Molecular Biology, Analytical Chemistry, or related field interested in integrated plant metabolomics and proteomics. Hands
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-scale biological datasets derived from both the host and the microbiome, employing advanced statistical methods and cutting-edge artificial intelligence techniques to uncover novel insights
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | 11 days ago
A doctoral degree in neuroscience or a related STEM field Prior experience in systems neuroscience using animal models A solid foundation in quantitative data analysis and statistics Programming
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large multi-dimensional datasets using statistical tools such as positive matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric
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student assistants and contribute to shaping the CRC’s research direction Your Profile PhD in computer science, neuroscience, machine learning, or related field Strong programming skills in Python and
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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
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Identification of soil invertebrates (e.g. mites, springtails, insects) using modern and classical techniques Laboratory analyses of soil properties Statistical analysis of complex ecological datasets Presentation
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PhD or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated experience in computational and statistical