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2025. Profile A PhD (or equivalent doctorate) in Business Administration, Management, or a related field (e.g., Psychology, Sociology, Engineering, or Economics). A strong publication record (or
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contributing to solutions in the global energy landscape. If you excel in collaborative environments and can bring expertise in some of the areas listed above, we encourage you to apply. Qualifications PhD in
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Location: Sofia, Sofia 1784, Switzerland [map ] Subject Areas: Computer Science / All areas Quantum Computing / Quantum Computing Artificial Intelligence Machine Learning / Machine Learning Natural
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Applicants should have recently earned a PhD in Economics and should show interest in the topics of the group. The preferred candidate has demonstrated her or his potential to conduct high-quality research
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Apply machine learning techniques for data analysis and time-series forecasting Collaborate in a multidisciplinary team to accelerate functional thin film development Your work will be part of a larger
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protein binders, investigate the effects of mutations on protein structure and function, and apply protein representation learning to uncover hidden links in the dark proteome. At the SIB Swiss Institute
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protein binders, investigate the effects of mutations on protein structure and function, and apply protein representation learning to uncover hidden links in the dark proteome. At the SIB Swiss Institute
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one of the programmes. It is home to a community of over 100 PhD, postdoctoral and Professorial researchers working on diverse themes related to sustainable cities and resilient infrastructure systems
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, including student tutoring and seminars. You will organize at least one full-week excursion for students and PhD students to visit the most interesting objects on site. Profile You are holding a university
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PhD in Computational Materials Physics or a related area is required. Experience with electronic structure calculations is essential. Familiarity with the use of machine-learning tools in materials