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to the group’s open-source software, and participation in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, computer
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analyses. The postdoc will be hosted at TDB, co-supervised by both groups, and will work at the interface of scientific computing, machine learning and particle physics. Project description Searches for dark
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. Plant science/ecology, especially related to forest ecosystems. Computer programming. Data analysis (machine learning, statistics, numerical analysis, time-series analysis, etc.). Quantitative methods in
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, which provides a great opportunity to be involved in challenging development projects. Qualifications To be qualified for the position, you must hold a PhD degree in Control Engineering, Computer
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and collaborative researcher who enjoys working across disciplinary boundaries, takes independent responsibility for a research agenda, and communicates clearly with both computer scientists and social
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Engineering, Computer Engineering, Mechatronics Engineering, Physics, Electrical Engineering, Chemical Engineering, Mechanical Engineering or other related subjects. Experience working on experimental
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subject. Proven experience with X-ray imaging/diffraction techniques, e.g. XRD-CT, 3D-XRD, µ/nanoCT, STXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability
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related subject. Proven experience with X-ray imaging techniques, e.g. µCT, nanoCT, TXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability to work both
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to hold a PhD in computer science or a related subject or have equivalent qualifications from abroad. The PhD must be completed before a decision to appoint an applicant is made. The candidate must have
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, ROS) Solid skills in numerical analysis Advanced knowledge of computer vision Experience in human–robot interaction Particularly Meritorious It is particularly meritorious if the applicant has: A PhD