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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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: 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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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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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
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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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change #utilize a participatory system dynamics modeling to match resilience patterns with best-fit learning cases from various regional contexts in Europe #develop a resilience performance framework for
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research collaborations with colleagues at the institute. Additionally, we expect postdocs to teach one course per semester. What we expect from you: An excellent PhD in Psychology, Education Sciences
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-scale controllable, and cost-efficient disease models by bringing together experts in physical chemistry, physics, bioengineering, molecular systems engineering, machine learning, biomedicine, and disease