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Field
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structural development over time at the group, sub-group, and individual level (e.g., using normative modelling and clustering approaches to parse heterogeneity). The candidates will further have the
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of PhD students in the project Profile We are seeking highly motivated candidates with strong achievements and a proven track record. Applicants must have: A PhD in physics, chemistry, materials science
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QUALIFICATIONS PhD in Biochemistry, Molecular Biology, Plant Biology, or a related field; Proven experience in the field of plant medicinal natural product biochemistry; Proficiency in molecular cloning, protein
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Bioinformatics, Molecular Biology, Biochemistry, Computer Science, or related field Special Skills, Knowledge, and Abilities: Required: Candidates must hold a doctoral degree (PhD, MD, or equivalent). Applicants
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& Desirable Criteria Essential A PhD in physics, electrical engineering, or other relevant subjects. Candidates must have submitted their doctoral thesis before starting in post. The ideal candidate will have a
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Python and Pytorch as well as deployment on GPU clusters. A strong publication record in graph neural networks, geometric deep learning, representation learning, machine learning–based molecular/materials
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of developing a knowledge cluster as a model for transition around the UK and internationally. This will build on the network and findings developed in an existing workshop series that brings together farmers
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biosynthetic gene clusters (BGCs). Studies focusing on the role of these infection-mediating genes are typically limited to specific pathogenic taxa and seldomly consider the overall infective competence
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toxins, antimicrobial resistance genes (ARGs) and biosynthetic gene clusters (BGCs). Studies focusing on the role of these infection-mediating genes are typically limited to specific pathogenic taxa and
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computational workflows on a high-performance cluster. You will test hypotheses using data from multiple sources, refining your approach as needed. The role also involves close collaboration with colleagues