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1-year fellowship in Shoebill Conservation Genetics with support for a further 3-year PhD fellowship
is rare, but precise numbers are lacking. The research will use molecular genetic tools to analyze the number of individuals in the Bangweulu Wetlands, their genetic isolation, and how genetically
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leading role in developing and implementing predictive algorithms designed to identify those most at risk from extreme heat, as well as offering personalized adaptation advice --- translating rich multi
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by combining psychological profiling, biological lab data, physiological time series, and sensor data. The postdoc will play a leading role in developing and implementing predictive algorithms designed
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.), microbial genetics, and/or bioinformatics are advantageous. As a doctoral researcher, you will furthermore assist master students and be involved in teaching activities.
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optical simulation skills (Preferably in Zemax) Strong programming skills (preferably in Python) Experience in deep learning algorithms is a plus Ability to work in a highly international team and
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biology / X-ray crystallography, protein design, natural product analysis (LCMS, NMR etc.), microbial genetics, and/or bioinformatics are advantageous. As a doctoral researcher, you will furthermore assist
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role of drug transporters and drug-metabolizing enzymes in these processes. Both transporters and enzymes are influenced by multiple factors, including naturally occurring genetic variants, which
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developmental biology, neurobiology, genetics as well as computational and systems biology. With over 30 groups, about 150 PhD students and over 500 employees, we are a lively and dynamic international community
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). Applications from candidates without documented hands-on mouse experience will not be considered. The project also includes high-throughput metabolic profiling of genetic perturbations, computational data
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, including the use of CRISPR-engineered cancer cell lines and metastatic models. In addition, the project integrates high-throughput metabolic profiling of genetic perturbations, computational data analysis