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Field
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, innovative research program particularly in the field of systems immunology applying novel high-resolution technologies, and/or computational analysis methods and artificial intelligence/machine learning is
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interdisciplinary desire to learn and willingness to cooperate, openness for internationalization and diversity, very good verbal and written English communication skills as well as the absolute determination
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dynamism. Its status as a comprehensive university allows for multidisciplinary learning and teaching and has great potential for internationally renowned, interdisciplinary research. Almost all of its
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of study Good Java and/or Python programming skills Machine learning knowledge and experience Experience with Static Analysis is recommended Good language skills in German and/or English What you can expect A
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advanced statistical/chemometrics and machine learning tools, iv) to couple metabolome data with other omics datasets (e.g., genomics, lipidomics, metallomics, and others). Main target areas are drug
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machine learning/artificial intelligence methods in combination with complex network analysis tools to predict and model interactions between food and biological systems Further scientific development
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-driven energy systems research – scalable, transparent, and interoperable. Your tasks in detail: Development of a structured description format for the unambiguous and machine-readable characterization
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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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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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? You are studying Mechanical Engineering in the field of Aviation or Shipping. Do you have knowledge of design and machine elements? Are you proficient in CAD and maybe even have first experiences in FEA