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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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clinical workflows and validate the established systems in tandem with clinical partners. About You You will possess a PhD (or be nearing completion) in mechanical, electrical, or biomedical engineering, or
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at scale. About You Applicants should preferably have an MSc/PhD in Computer Science/Engineering. They should have expertise in distributed systems and computer networks. Excellent knowledge and practical
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position from 01.10.2025 of a Postdoc Position at the Research Group Data Mining and Machine Learning at the Faculty of Computer Science, University of Vienna under the supervision of Prof. Claudia Plant
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PhD (or close to completion) or research qualification/experience equivalent to PhD level in the relevant subject area for the research programme; with a productive track record and have experience
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About the Role We are looking for a Postdoctoral Research Assistant to work with Dr Chema Martin on a Human Frontiers Science Program Research Grant project entitled “Evolutionary Biophysics
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Fixed-term: The funds for this post are available for 12 months. Applications are invited for a Research Assistant (RA) to join the Prorok Lab in the Department of Computer Science and Technology
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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at the intersection of education, mental health, and developmental science. The successful candidate will contribute to a major research programme investigating how educational experiences shape mental health from
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We are seeking a talented and motivated researcher to join the Mead Group to contribute to a major research programme focused on characterisation of in vivo models of myeloid neoplasms and