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simulations using, e.g., COMSOL, Lumerical, or other Maxwell solvers. Experience with machine learning algorithms is an advantage but not required. General qualifications Scientific production and research
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approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed at uncover the key traits that define successful microbial biofertilizers
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the above-mentioned research areas (e.g. scp-MS, cell heterogeneity, computational proteomics, etc.) Foster national and international collaborations, both outside and within the university Teach in
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PhD students. Contributing to the teaching at the department to build your teaching portfolio for applying to academic positions. Participating actively in the research community, including attending
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qualification, you must hold a PhD degree (or equivalent). The successful candidate must moreover exhibit the following professional and personal qualifications: Strong background within machine learning learning
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verification. runtime analysis and reconfiguration of in-vehicle TSN networks. Co-supervise MSc and PhD students. Optionally contribute to teaching and proposal preparation. Required qualifications: As a formal
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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. Technology for people
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qualification, you must hold a PhD degree in computer science, software engineering, biomedical engineering, data science, or a similar field. Your project management skills include: Experience in technical
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the project. Qualified candidates should have: A PhD degree in Computer Science, Electrical Engineering or equivalent. Research interests and a scientific track record in Edge Computing research fields, such as