108 computer-science-programming-languages-"Prof"-"TU-Dresden" PhD positions in Germany
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11 Dec 2025 Job Information Organisation/Company Universität Siegen Research Field Computer science » Informatics Researcher Profile First Stage Researcher (R1) Country Germany Application Deadline
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Application Deadline 15 Jan 2026 - 23:00 (UTC) Type of Contract To be defined Job Status Part-time Hours Per Week To be defined Is the job funded through the EU Research Framework Programme? Not funded by a EU
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program in and beyond the fields mentioned above Competitive, interdisciplinary environment with a track record of intense mutual collaboration Individual training-through-research, program extends
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physics, materials science, computer science or a related discipline background in one or more of the following areas is desired: X-ray or electron imaging techniques, and image processing proficiency in
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Ingolstadt. The salary is prescribed by the framework of the collective agreement (TV-L), Level 13 (75%). The research group Reliable Machine Learning (headed by Prof. Felix Voigtlaender) is part of
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background in bioinformatics, systems biology, molecular biology or a related field You should have strong programming skills (preferably in R and Python) and familiarity with Linux Experience in constraint
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Requirements: Applicants should hold an MSc or Diploma in Engineering, Computer Science or a related discipline. Background in Machine Learning and Artificial Intelligence. Strong programming skills (Python
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independent work and effective collaboration, particularly during measurement campaigns at synchrotron and neutron facilities. Experience with programming languages such as Python is advantageous. Participation
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. The communication language of the lab is English. The group interacts tightly with the Research Group Cognitive Neurophysiology (PI M. Yoshida; in-vitro/in vivo electrophysiology & computational neurosciences) as
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practical lab position, so applicants with only (bio-)informatics background will not be considered. For inquiries, please contact: Prof. Thomas Weide ( weidet@uni-muenster.de ; Thomas.Weide@ukmuenster.de