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machine-learning-based approaches, and to evaluate the thermodynamic costs of quantum operations. You should work effectively as part of a team and engage constructively with collaborators. You will hold a
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Biology with both high-throughput experimental (proteomics and genomics) and integrative computational (network analysis and machine learning) methodologies, aiming to understand gene functions and their
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. QUALIFICATIONS PhD in Civil Engineering, Environmental Science, Computer Science, or a related field Research experience in hydrology, geospatial analysis, and machine learning Skills of scientific writing and
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Integrate multi-omics data with clinical, cognitive, and imaging phenotypes in longitudinal cohorts Develop and apply statistical and machine-learning models (e.g., mixed-effects models, survival analysis
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, machine learning, and/or computational biology to be able to work within established research programmes. They will have excellent communication skills, including the ability to write for publication
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the performance and scalability of large-scale molecular dynamics simulations (e.g. LAMMPS) using machine-learned potentials (e.g. MACE) through algorithmic improvements, code parallelization, performance analysis
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programme focused on applying AI‑driven analysis to in situ advanced microscopy of fibre‑based materials. The project aims to develop and deploy machine learning tools that extract real‑time structural and
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to completion) or possess equivalent research experience in a relevant computational field such as data science, artificial intelligence, machine learning, computer science or statistics. They will bring strong
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a team-oriented research environment. PREFERRED QUALIFICATIONS Prior experience in one or more of the following areas: longitudinal data analysis, survival analysis, spatial methods, machine learning
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multiple symbolic fields, including official political discourse, academic debates and selected cultural outputs. Methodologically, it adopts a mixed-methods approach, combining machine-learning–enhanced