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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 6 days ago
research team. The ideal candidate should have: A PhD/DPhil degree (or comparable) with a background in theoretical physics, applied mathematics or related disciplines from a recognized university; Prior
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participants, and mathematical / statistical modeling. Requirements for employment are a completed PhD degree in a relevant field (Linguistics, Cognitive Science, Psychology, Philosophy, or similar), near native
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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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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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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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: 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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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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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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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