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of food web components, from primary producers to fish, during open-water (summer) and under-ice (winter) conditions. Analysis of biomarkers (PUFA and cyanotoxins) in biological samples using
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component: - Undertake advanced training in qualitative, quantitative, participatory and geospatial research methods. - Participate in seminars, scientific meetings and training activities organised by
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and metabolic interactions with mammalian cells. Possible project elements include: Microfluidic synthesis of polymer capsules and microgels Encapsulation of enzymatic reaction networks, metabolic
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and/or Python; experience with Unix/Linux environments and bash is considered an advantage Prior experience in the preprocessing, analysis and interpretation of omics data and a strong interest in
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latent profile analysis. Your main tasks and responsibilities in this project are: As a PhD candidate, you will coordinate this multicentre observational clinical study. In Amsterdam UMC you will include
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£26,805 per year, and includes the PANDA DFA training programme as part of the 2026 Cohort (https://www.bangor.ac.uk/panda ). This project is linked to UK National Nuclear Laboratory (UKNNL), who will
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comprehensive and innovative methods to directly test palaeoecological hypotheses using both fluid dynamics simulations and experiments, which will be applicable across the study of life on Earth. https
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molecular or cellular biology - Excellent English language skills - Prior experience with image analysis or patch-clamp electrophysiology is highly valued How to apply: Please send: a CV and short expression
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conditions, by bridging disciplines, from artificial intelligence, microelectronics, neuroengineering and nanoscience, to single-cell, imaging and molecular analysis, functional genomics and cell biology in
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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high