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experiments utilizing state-of-the-art approaches such as: Animal models of metabolic diseases and atherosclerosis Flow cytometric analysis of immune cell populations from murine tissues using full spectrum
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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research environment is highly collaborative and interdisciplinary, spanning genome biology, computational analysis, and translational cancer research. Members of the lab gain expertise in next-generation
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Knowledge and experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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bioinformatics/computational data analysis Facts & figures Workplace MDC Berlin-Mitte Salary Remuneration will be according to the TVöD Bund, depending on the personal requirements, up to the fee group E13 Desired
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characterization techniques. A strong interest in structural biology and the motivation to learn cryo-electron microscopy (cryo-EM). Familiarity with bioinformatics for sequence or structure analysis
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their impact on bladder function under physiological and pathological conditions. Work will include data acquisition, analysis, and interpretation, as well as collaboration with clinicians for human
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. Strong knowledge of quantitative and/or computational research methods, ideally in econometric analysis or optimization and simulation models. Preferable knowledge in Python and STATA. A collaborative team
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and medical image analysis. The interdisciplinary and collaborative research environment at the DKFZ also results in excellent opportunities for computational and data scientists with interest in