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further both professionally and personally in an interdisciplinary setting. Position DWI is looking to fill the position as soon as possible: Research Scientist Machine Learning Engineer - AI-Powered Image
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into real-world applications in Geriatronics. Your Profile PhD in Robotics, Mechanical Engineering, Electrical Engineering, Computer Engineering, Mechatronics, or a closely related field. Proven experience in
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work at international conferences, and publish in leading journals. Through its Graduate Centre and Talent Factory, TUM supports PhD students and Postdocs by providing a dedicated qualification program
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on these considerations, solutions will be developed and implemented to create an advanced testing platform for the comprehensive evaluation of the long-term stability of invasive brain-computer interfaces. Your task will
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of e.g. proteomics, lipidomics, or metabolomics data Requirements: Candidates must hold a master’s degree in Data Engineering, Data Science, Bioinformatics, Informatics, or a related discipline. Essential
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, ranging from life sciences to engineering. For more information, visit our webpage www.epc.ed.tum.de/en/mfm. Your profile - M.Sc. degree in informatics, physics, chemistry, or engineering (candidates who
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. Contact Prof. Holger Boche, Technical University of Munich, School of Computation, Information and Technology, Chair of Theoretical Information Technology, Theresienstrasse 90, 80333 Munich. https
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• You have a degree (Master’s or equivalent) in Civil Engineering or Mechanical Engineering with a strong focus on continuum-solid mechanics and computational methods. • You have experience in and
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dynamic team. As part of the newly funded ERC Synergy consortium EPIC, you will develop scalable and robust software to train and apply AI models for regulatory genomics. About us The Chair of Computational
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technical field, such as mechanical engineering, computer science, transportation systems, or civil/environmental engineering with a focus on traffic engineering, with very good grades. You bring solid