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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
, the University of Copenhagen and the MAX IV synchrotron. You will work with an international team of mathematicians, crystallographers and data scientists. The project aims to transform small-molecule structure
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to two PhD students in Statistics for the research project “Next-Generation Latent Variable Models for Social Data Science”. Application deadline: November 4, 2026. We are seeking one to two PhD students
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In this PhD position, you will help design the next generation of circular plastics systems by combining hands-on polymer processing with data-driven modelling. The PhD study is a full-time, fixed
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the BioGeomorphology Laboratory flume, field datasets from restored and natural saltmarshes across the UK, and expertise from researchers in coastal ecology, hydrodynamic modelling, AI, and data science. Objectives
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learning, computing, data science, biomedical engineering, or a related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with
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spectrometry workflow, from sample preparation and digestion through LC-MS/MS acquisition to data analysis and interpretation; a laboratory animal science certification (Article 9, rat/mouse) that is valid in
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control, proximity engineering and quantum transport. Analysis and interpretation of experimental data. Presentation of results at international conferences and preparation of scientific publications
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: Experimental evaluation of biomarker behaviour under differing rehydration strategies (i.e. water-only versus electrolyte-supported rehydration). Data analysis and classification framework Data collected across
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methods like (panel) survey, lab experiments focus groups, and data donation. Each PhD Candidate will write a paper-based dissertation and strive to publish the results of the individual sub-studies in
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Are you excited about the future of wearable healthcare? Join us to merge microfluidics and contact lens technology, developing smart lenses that enable controlled tear fluid collection and analysis