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learning, with approximately 240 full-time researchers, including 80 PhD students, and 4,500 Bachelor’s and Master’s degree students. The school’s activities are characterised by a high degree of
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investigating how creative, experimental and practice-based learning cultures can be developed in vocational education. In relation to research, applicants should document: Experience, skills and achievements
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of importance for changes in effective populations sizes and genetic diversity patterns. Qualifications Ideally you have a PhD in natural sciences with a strong research background and several years of work
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-impact publications and knowledge dissemination in flagship forums Your profile The ideal candidate holds a PhD in Electrical Engineering, Electrochemistry, Energy Systems, or a closely related field
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interdisciplinary, collaborative project at the interface between nucleic-acid chemistry, DNA/RNA nanotechnology and cell biology. Your profile Applicants should hold a PhD in chemistry, molecular biology
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, you will contribute to research-based teaching and the supervision of student projects. Skills in mathematical modelling and machine learning of relevant physical glacier processes (ice sheet and
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project. 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
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. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and process-based radiative transfer models
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competencies The ideal applicant profile should demonstrate expertise in one or more of the following areas: optimization algorithms (heuristics, metaheuristics, exact methods), learning-based approaches
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focus on educating engineering students at all levels, ranging from BSc, MSc, PhD to lifelong learning students. We have about 300 dedicated employees. Read more about us at www.energy.dtu.dk