84 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"SciLifeLab" positions at Technical University of Munich in Germany
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details of two referees The deadline for application is March 1st, 2026. For more information about PFT group, please check on our website Particle and Fiber Technology The position is suitable for disabled
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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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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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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for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. Data Protection Information: When you apply for a position
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, Mechanical Engineering, Electrical Engineering, Computer Engineering, or a closely related discipline. Strong research interest in telerobotics, shared control, human–robot interaction, or networked control
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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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qualified women. About the position The position contains both teaching duties and participation in research projects. The research project topics focus on improving object recognition through computer vision
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processing of personal data in connection with your application, http://go.tum.de/554159. By submitting your application, you confirm that you have taken note of the data protection information of the TUM
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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