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to unfused enzymes. The successful candidate will Develop coarse-grained (CG) models for CAR and other enzymes of the cascade based on atomistic simulations provided by the project team. Run Brownian dynamics
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meetings, conferences, and as scientific papers Contribute to educational events, such as university lectures, JSC courses and hackathons Your Profile: Excellent masters degree and subsequent Ph.D. degree in
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to different domains. Specifically, you will: Develop, implement, and refine Machine Learning (ML) techniques for self-supervised Deep Learning (DL) for scientific and large-scale datasets Implement parallel ML
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motivated team at Forschungszentrum Jülich, which is one of the largest and best-equipped research facilities in Europe You will have the opportunity to participate in project meetings and education events
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Jülich, which is one of the largest and best-equipped research facilities in Europe You will have the opportunity to participate in project meetings and education events organized in the frame
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(ML) algorithms with a strong focus on neural networks (NN) to create a versatile image processing tool as well as to develop new, advanced ML-supported imaging techniques. Your tasks in this exciting
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(demonstrated by e.g. teaching experience or supervising student work) Very good verbal and written communication skills in English Willingness to regular business trips within the Rhine-Ruhr area Our Offer: We
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highly motivated group and an international and interdisciplinary working environment in one of the largest research institutions in Europe The possibility to develop your own research program in line with
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actively help in shaping the change! We support you in your work with: The candidate will work in an internationally recognized research group in this field offering the candidate the chance to develop
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self-motivated way of working but also excellent teamwork skills Readiness for regular business trips High motivation to take on responsibility and develop own research ideas Our Offer: We work on the