234 scholarship-vacancy-for-phd-in-computational-physics Postdoctoral positions in Denmark
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publication in peer-reviewed journals, and a proactive attitude toward dissemination of research outcomes. Qualification requirements Appointment as postdoc requires academic qualifications at PhD level. Who we
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into the modelling approach. Supervision of PhD student in regards to project management of field trial and greenhouse experiments Prepare and publish scientific articles in high-impact journals. The postdoc’s duties
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, the applicant chosen is expected to be physically present on a regular basis and actively participate in the teaching and research activities of the Department. Qualifications The applicant must hold a PhD or the
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: Background in Data Science, Computer Science or related fields; Working experience in implementing AI models (not just loading pre-trained model). PyTorch framework is preferred; Experience with APIs
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highly motivated candidate who meets the following qualifications and characteristics: PhD (completed or soon to complete) Software Engineering, Computer Science, Embedded Systems, Artificial Intelligence
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experimental techniques. As a formal qualification, you must hold a PhD degree (or equivalent). You must have: Documented expertise in either computational protein design or wet lab techniques, with a
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/sintering of functional ceramics Have knowledge of SOEC materials and technology As a formal qualification, you must hold a PhD degree (or equivalent) in mechanical engineering, materials science, or a
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communication skills in English, both written and spoken. As a formal qualification, you must hold a PhD degree in physics, chemistry, materials science, nanoscience or equivalent. We offer DTU is a leading
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PhD students and postdocs at DTU Energy and DTU Physics, which will realize your designs in the lab, provide experimental input to your modelling and ultimately use the sensors to detect the activity in
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. The research will bridge both established and emerging technical expertise within the section, encompassing areas such as FPGA and neuromorphic computing, Edge AI, machine learning, power electronics, and self