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We are recruiting a postdoctoral research scientist to lead virus evolution and bioinformatic data analysis for our program on wastewater surveillance for pandemic pathogens. The world has never
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, experience managing and analysing ancestrally diverse genomic datasets, and expertise in computational genetics, including variant annotation and genome-scale analyses. Proficiency in R or Python, excellent
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Full time: 25 Hours per week Fixed term: 12 months We are looking for a candidate to join the University of Edinburgh to conduct research on Machine Learning, Reinforcement Learning, or LLM orchestration, with applications to Finance. This post is advertised as full-time (35 hours per week). We...
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skills and knowledge of biodiversity to plan and lead research on how biodiversity change is unfolding in the Anthropocene. This project will assess and analyse existing biodiversity and ecological data
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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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well as access to the group dedicated computing cluster environment with H100, L40s, and A40 GPUs. This post is funded by the UKRI Future Leaders Fellowship, a flexible long-term public funding scheme
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About the role The Kelly lab is excited to announce a new post-doctoral position in computational biology. This position is funded as part of an international consortium of scientists who
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research centre well-known for its close-knit community, friendly atmosphere, and outstanding research support. We are seeking a post-doctoral research associate with experience in computational approaches
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to artificial intelligence (AI) (e.g. computer science, engineering, Statistics, and mathematics etc.) The post is available for 30 months, starting on 1 September 2025. If you are still awaiting your PhD to be
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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