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frameworks, applying existing frameworks, and implementing novel methodology in shared code repositories. You will also assist in instructing and guiding the research of MSc and PhD students. Qualifications As
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to our position as Postdoc. At the Faculty of Engineering and Science, Department of Chemistry and Bioscience, a position as Postdoc in membrane manufacturing and membrane processes is open for
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research assistant requires a master’s degree and the position as postdoc requires a PhD degree. In both cases an educational background within robotics, mechanical engineering, electrical engineering
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the areas of medical/surgical robotics, artificial intelligence, and control. The position as research assistant requires a master’s degree and the position as postdoc requires a PhD degree. In both cases
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) Collaborate within the CPE research group and our local, national and international networks Report your results in peer-review scientific publications and international conferences Teach and supervise PhD, MSc
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Postdoc position to support international research and capacity-building projects employing elect...
of large-scale EM data for groundwater mapping. Teaching and training of Ethiopian partners and students in EM methods, data processing workflows, inversion software, and geological interpretation
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) Collaborate within the CPE research group and our local, national and international networks Report your results in peer-review scientific publications and international conferences Teach and supervise PhD, MSc
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, Computer Science, Software Engineering, Applied Mathematics, Robotics or a related field. Qualification requirements Appointment as postdoc requires academic qualifications at PhD level. Who we are The Department
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-impact peer-reviewed journals and contributing to project deliverables Engaging with academic, industry, and policy stakeholders to disseminate findings. We are looking for candidates who offer: A PhD in
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uncertainty from climate projections into land-use forecasts. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models