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Field
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) Participation in international conferences (including presenting your research results) Preparation of scientific publications and project reports Supervision of PhD students and other students Support in
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molecular properties for comparison with experimental results. Requirements: Completed university degree (M.Sc or Diploma degree) in Chemistry or a closely relatet field and PhD / Doctoral degree in Chemistry
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collaboration with our clinical colleagues for investigating visual motion in a group of healthy subjects. The successful applicant holds a PhD degree (or equivalent) in a relevant academic area such as applied
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conferences (including presenting your research results) and preparation of scientific publications with Peer-Review Your Profile: Completed university masters degree (physics/chemistry) with a PhD Strong
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projects of the research group Qualification Required: A diploma and a PhD in microbial natural product chemistry Hands-on experience and a strong understanding of metabolomics/dereplication of natural
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reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming languages (C++, Python, or Julia) is highly relevant. Knowledge
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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: According to §110 (4), sentence 3, the BerlHG provides academic staff with an appropriate amount of time within their working hours for their own further academic qualification. What we are looking for PhD
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areas is expected: numerical analysis, scientific computing, model reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming
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decision‑support tools to inform management and policy, ensuring that monitoring strategies are fit‑for‑purpose. Your profile You hold a PhD in marine ecology, molecular ecology, bioacoustics, or a closely