62 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr" positions at Technical University of Munich in Germany
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biochemists developing the labeling agents, data analysts developing analysis algorithms and physicists developing hardware. The candidate The candidate should have a firm base in in vivo imaging and cell
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the VIOLET research framework Work closely with clinicians and data scientists to ensure the developed systems meet clinical needs and are validated against real-world scenarios Mentor and supervise PhD
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Robot Learning (ID: TUEILSY-POSTDOC20251219-RL) Robots that learn from data promise greater autonomy and performance, but their deployment in the real world hinges on the ability to guarantee safety
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of extension, depending on performance and project needs. **Qualifications** • For Doctoral Candidates: Master’s degree in Computer Science, Information Systems, or Mathematics. **Applicants must demonstrate
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preference in case of generally equivalent suitability, aptitude and professional performance. Data Protection Information: When you apply for a position with the Technical University of Munich (TUM), you are
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groups. Applicants with disabilities will be given preference in case of equal qualifications. More information about our research and team can be found here: www.lse.ls.tum.de/fmp. Application – Please
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. Publish and present findings in international journals and conferences. Supervise and mentor junior researchers and students. Profile PhD in Computer Science, Biomedical Engineering, Data Science, or a
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young scientists worldwide to German research institutions. For more information, see here . The position is suitable for disabled persons. Disabled applicants will be given preference in case
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at the Professorship of Energy Management Technologies are focusing on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make
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data are essential. This has also been appreciated with the nomination “technology of the year 2019” by the journal Nature Methods. Our research group employs state-of-the-art single cell sequencing