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is seeking a PhD student to join an ongoing Royal Society–Research Ireland University Research Fellowship project focused on Machine Learning for the Design of Additively Manufactured Two-Phase Heat
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) Evidence of scientific writing and publications is a plus Excellent communication and data presentation skills Fluent in English (German is an advantage) Motivated, collaborative, and able to work
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Medicine (WCMTM) and SciLifeLab in the University of Gothenburg. and is tightly connected to a broad network of international collaborators. Duties Develop and perform high-resolution spatial transcriptomics
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orientation with compositional design, the project will investigate how directional control over framework domains influences charge transport, optical response, and catalytic performance. Applications include
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satisfactory performance and funding availability. Applicants should possess a Ph.D. degree in Public Health, Nursing, Health Science, Social Sciences, or a related discipline. They should have an excellent
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Professor in the School of Nursing (Ref.: 537246), to commence as soon as possible, on a two-year fixed-term basis, with the possibility of renewal subject to satisfactory performance and funding availability
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In a fusion reactor its walls must endure intense heat fluxes as well as a constant bombardment of neutrons and plasma species. Traditionally solid materials such as tungsten have been the primary
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. Interest in high-performance computing and parallel algorithms. Fully funded 4-year PhD position at KU Leuven and EnergyVille. Research at the forefront of future converter-dominated power systems. Access
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access to advanced laboratory equipment and solid funding opportunities. You will be offered secure employment, high-quality supervision, and room to grow, both as a researcher and as a person. The
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orientation with compositional design, the project will investigate how directional control over framework domains influences charge transport, optical response, and catalytic performance. Applications include