18 genetic-algorithm-computer "Integreat Norwegian Centre for Knowledge driven Machine Learning" PhD positions at University of East Anglia
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Primary Supervisor - Prof David S Richardson Scientific Background Genetic variation within populations is essential to their ability to adapt and survive, but most mutations that change function
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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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straightens the fingers but does not treat the underlying biology; recurrence is common and repeat operations carry escalating risks to hand function. With genetic risk variants now linked to the disorder
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-on experience in both laboratory and computational approaches, equipping you with a strong skill set for a career in evolutionary genetics, genomics, or bioinformatics. Person Specification This project is ideal
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(optional). Person specification: Prior experience in computer coding (e.g., Python, SLiM), AI modelling, and understanding of evolutionary or conservation genetics / genomics is desirable. Good teamwork
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the decline by introducing new red squirrels from continental Europe, representing an unusually long-running attempt at genetic rescue. How all of this has affected the genetic make-up, fitness and ancestry
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of Berberis in major wheat growing areas, (ii) assess the genetic diversity of locally adapted Bhutanese wheat landraces and their typically higher resilience to rust infection, and (iii) develop a spatial
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We seek an enthusiastic and inquisitive individual with a background in a subject aligned with the Biological Sciences, Molecular Biology, Microbiology, or Genetics. Entry Requirements At least UK
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colibactin-producing bacteria thought to induce colorectal cancer. In contrast, the aetiology of prostate cancer is largely unknown, with the exception that genetics and race are established components
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-specific TEM protocol will be used to reveal their subcellular localisation. This work will be done at UEA and IOCAS (Prof. Shan Gao). Objective 2: Using the genetically tractable model diatom Phaeodactylum