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environment for PhD candidates as well as an outstanding research-based training programme, preparing students for a career in academia, science management, or industry. Each PhD candidate is affiliated with
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and setting up of gas lines and synthetic processes. You help initiate cooperations/collaborations with industry partners. Your Profile Master's degree (or similar) in chemistry, chemical engineering
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Engineering, or a related discipline - Solid understanding of fluid dynamics and/or electromagnetism - Programming experience (preferably Python) - Interest in machine learning and scientific computing
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, United Kingdom Supervisor: Dr. Ivana Savic Focus: computational materials modelling Background: physics, computational materials science. or a closely related discipline Apply: https://mgician.eu/research/doctoral
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Max Planck Institute of Molecular Physiology, Dortmund | Dortmund, Nordrhein Westfalen | Germany | about 1 month ago
, Computer Science, or related fields. Visit the IMPRS-LM website for more information about the program, the application process , and the list of research group leaders currently offering positions
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with team members and colleagues. Essential qualifications: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep
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Your Job: At the Electrocatalysis department of Prof. Karl Mayrhofer, we offer a PhD position within the team Nanoanalysis of Electrochemical Processes. Lead by Dr. Andreas Hutzler, the team is
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to work in. Research groups: Computational Neurosciences Computer Graphics and Ecological Informatics Computer Networks Computer Security Databases and Information Systems Data Fusion Data Science
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) • Experience with plant water relations, plant hydraulics, or hormone signalling • Biochemical or molecular biology techniques • Experience with imaging, phenotyping, or data-driven analysis • Willingness
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Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models, adversarial attacks, and