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a doctorate. We are looking for: candidates with a Master’s degree in mathematics or a closely related field and with a strong background in probability theory. Prior knowledge in spatial stochastic
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for diversity Desirable knowledge and skills include: o Understanding of the principles that define DNA, RNA, protein structures, functions, dynamics and interactions o Experience in plant work
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necessary knowledge and a broad range of skills for the successful completion of the project. Basic knowledge of data analysis or programming and good English skills are desirable. We value independent
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the field of Biotechnology/Biology/Bioprocess engineering or related field Knowledge of genetic engineering, protein production and cell-free approach as well as bioprocess engineering, bioproduction
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international collaborators’ labs. The applicant should: • have interest in developing and/or applying novel chemical probes to investigate biological functions, • have sound knowledge of organic chemistry, both
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using human primary cells Very good knowledge of written and spoken German and English Desired Practical experience with the application of microphysiological systems Knowledge of bone physiology and
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Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference implementation of your machine learning pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with
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the field of biotechnology, bio-/chemical engineering, (bio) process engineering, bioinformatics, biophysics or biomathematics. Ideally you have Programming skills and knowledge on machine learning and
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way of working and quick comprehension; ability to quickly familiarize yourself with new concepts Enjoy scientific work in a cross-domain context. Good knowledge of programming languages (e.g. Python, R
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to impart both scientific and methodological knowledge and offers the opportunity to regularly present doctoral projects in internal events and benefit from scientific exchange. You can find information