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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
linear regression, mediation analysis, multilevel modeling, and/or latent variable models. Experience in managing and analyzing large datasets, and the use of generative AI tools for research purposes
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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
innovative methods of assessment and/or advanced statistical methods, such as multiple linear regression, mediation analysis, multilevel modeling, and/or latent variable models. Experience in managing and
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satisfactory performance and funding availability. Applicants should possess a PhD degree in epidemiology, biostatistics, applied mathematics, data science or other related disciplines. They should have strong
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as soon as possible for one or two years on temporary term basis, with the possibility of renewal subject to satisfactory performance and funding availability. Applicants should possess a PhD degree in
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carbide · Design experiments and studies for bipolar degradation of SiC devices · coordinate data collection and analysis · support the organization of dissemination events · assist in the preparation
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group. Duties and Responsibilities · work on a project related to silicon carbide · Design experiments and studies for bipolar degradation of SiC devices · coordinate data collection and analysis
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the possibility of renewal subject to funding availability and satisfactory performance. Applicants should possess a PhD degree in Biology or related disciplines, preferably with experience in virology research
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to: designing, implementing, and optimizing high-performance C++/C# software modules for real-time control, sensor fusion, and data analysis; developing unity‐based visualization and user-interaction interfaces
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performance. Applicants should possess a PhD degree in biological sciences or related fields, with expertise in bioinformatics and biostatistics, and a proven research track record on analysing viral evolution
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of Physics (Ref.: 532531). Applicants should possess a Ph.D. degree in Condensed Matter Physics. Experience in numerical techniques and analytical field-theoretical approaches is desirable. Applicants who