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bachelor and master programs, explicitly in the newly established M.Sc. program Human Factors Engineering. Qualifications We are looking for candidates who have demonstrated excellent achievements in
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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”) Supporting team members and collaboration partners with bioinformatic/computational tasks Managing and supporting international research projects with regard to organizing meetings and reporting to the funding
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the results, documenting the results, and summarizing the findings in a final report Your Profile: Enrolled in a Master’s program in chemistry, materials science, electrochemistry, or a related field Experience
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, Marine Chemistry, Biological Oceanography, Marine Geosciences, and Marine Observations works interdisciplinary within a joint research program. What will be your tasks? The successful candidate will work
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, enrolled in a Bachelor’s or Master’s program in economics, finance, data science, or a related field. Comfortable using Stata or Python/R (or other analytical tools). Detail-oriented, methodical and able
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for different application use cases Your Profile: Enrolled in a Master’s program in physics, materials science, electrical engineering or a related discipline Solid background in solid-state physics and/or
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applications for a Full Professorship (W3) in “Multimodal Imaging” (f/m/d) to be filled at the earliest possible date. We are searching for a researcher with an internationally visible, original research program
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! We
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be a member of the Faculty of Physics and Astronomy and the Faculty of Mathematics and Computer Science. The appointee is expected to play an important role in further enhancing the research