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a doctoral student with a strong background in machine learning, mathematics, and modeling, and an interest in biological systems. The successful candidate will join a project to understand and model
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analysis to better understand how molecular and cellular processes are coordinated across cells, tissues, and organ systems in human health and disease. You will be responsible for developing and applying
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mathematical skills in large-scale datasets • Research experience in cancer epidemiology or molecular epidemiology • Ability to work independently, be self-motivated, initiative, creativity and collaborative
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. Required qualifications: PhD in a field such as physics, systems biology, applied mathematics, machine learning, or related fields. Strong programming skills (e.g. Python) and experience with modern ML
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should have: a Ph.D. or similar working experience in Image analysis, Bioinformatics, Computer Science, Data Science, Engineering, Physics, or equivalent. Extensive (3+ years) experience of applying and/or
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lies in biology, it intersects with other disciplines such as medicine, computer science, mathematics, chemistry, engineering, and physics. The department employs over 200 staff members, including
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states and structural ensembles. The project builds on extensive expertise in the Piazza laboratory in quantitative proteomics, and proteome-wide analysis of protein structural changes. The PhD student
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, or a related field, who enjoys interdisciplinary work spanning wet-lab experimentation and computational data analysis. In addition to the aforementioned requirements for the position: A Master’s
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from molecular dynamics simulation trajectories in silico. On the wet-lab side, the position involves generating both fluorescence and mass spectrometry data and optimizing protocols for its analysis
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in advanced national postgraduate courses and training events. Qualification requirements The candidate should have a Ph.D. or similar working experience in Image analysis, Bioinformatics