396 machine-learning-"https:" "https:" "https:" "RAEGE Az" Postdoctoral positions in United Kingdom
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will work as a member of an interdisciplinary team (including experts in machine-learning and microbiology) to establish microfluidics-enabled microscopy assays on single bacterial cells to determine
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interdisciplinary team (including experts in machine-learning and microbiology) to establish microfluidics-enabled microscopy assays on single bacterial cells to determine their antibiotic resistance. Your work will
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will contribute to the development of a new simulation-based pre-training framework for building more robust and trustworthy machine learning-based clinical prediction models. Funded by the Medical
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. About the Role The post is funded for 3 years and is based in the Big Data Institute, Old Road Campus. You will join an interdisciplinary team of researchers spanning imaging science, machine learning
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and trustworthy machine learning-based clinical prediction models. Funded by the Medical Research Council (MRC) and the National Institute for Health and Care Research (NIHR), the project aims
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Location: Kavli Institute for Nanoscience Discovery Contract type: 1 year Fixed-term (with the possibility of an extension) We are seeking a Postdoctoral Research Assistant for the Gene Machines
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We are seeking a Postdoctoral Research Assistant for the Gene Machines’ group, led by Prof Achilles Kapanidis. The group is well known for developing single-molecule and single-cell fluorescence
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microbiology, and machine learning, you will identify AMR genes, pathogens of public health concern (including ESKAPE and WHO-priority organisms), and reconstruct metagenome-assembled genomes (MAGs). Across five
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experiments for investigating the neural mechanisms underlying habitual behaviours and learning adaptation to uncertainty. You will use fMRI and neurostimulatory techniques (ultrasound neurostimulation and/or
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classification algorithms including machine learning); and the output data and interpretability. The project “SORS in the community” is funded by the EPSRC (https://www.ukri.org/news/new-tools-aim-to-improve-early