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At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13 TV-L, part
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offering PhD positions for students with a background in data science, computer science, computational science, or a domain science with a strong focus on computational science, and an interest in training
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Description At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13
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of working in interdisciplinary contexts (desired) Our Offer The PhD position is awarded for three years, with the possibility of an extension of 12 months (pending a positive evaluation). Employment will be
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Additional information on beginning, duration and mode of study The starting date of the PhD project is flexible. The initial funding period is usually three years. Find out more at https://www.bgc-jena.mpg.de
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, the concept of a cross-university PhD programme involving non-university institutions was developed to enable the combination of different scientific and technological disciplines relevant to biomedical data
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | 1 day ago
information about pursuing a PhD or doctorate at BTU, please refer to the website of the BTU Research Department or contact the PhD Coordinator: stella.gypser@b-tu.de . Brandenburg University of Technology
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regulatory processes. Develop analysis pipelines for pre-processing, normalization, and statistical modeling of high-throughput sequencing data. Integrate and mine public datasets to complement in-house
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cells from different mouse models with accelerated aging phenotype. The work of the PhD candidate will include data mining and integration of these datasets with resulting identification of candidate
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on Responsible Data Science. The PhD positions will be at the intersection of Data Science and Social Sciences and will focus on topics such as Explainable & Fair AI, AI Auditing, AI Alignment, and AI Safety in