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on cell viability and DDR activation in established human cell models. The student will perform CRISPR screens to determine factors that affect resistance/sensitivity and follow these up with mechanistic
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chromatin profiling methods along with CRISPR/Cas9-meduated cell line engineering and various animal models. You will study the effects of the activation or depletion of chromatin-modifying enzymes using
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functional motifs are encoded in HS chains and how they influence their biological activity. Using gastruloids as a model system with which to study GAG structure/function relationships. Generating gastruloids
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marginal structural models will be extended with machine learning techniques for counterfactual prediction and to support sensitivity analyses Candidate The studentship is suited to a candidate with a strong
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cells or the tumor microenvironment reduces tumor growth and extends survival in preclinical models, underscoring their potential as dual-function therapeutic targets. To address this, we aim to develop
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place of a Research Proposal, you may submit a copy of this advertisement. One-page personal statement demonstrating your research experience, motivation for choosing a PhD project on post-quantum secure
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curriculum vitae. Please also send a copy of your full application directly to Prof Kendrick.
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| £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity invites applications from candidates with a robust foundation in data science, modelling, and
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(BGI) is one solution to help mitigate surface water flooding, and can also provide a wider range of benefits related to biodiversity, health and water quality. Robust models are needed for comprehensive
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programming and modelling frameworks (JuMP, Pyomo, Yalmip, GAMS, etc) Experience with unbalanced distribution system analysis tools (e.g., OpenDSS, Cyme, Gridlab-D, PowerModelsDistribution.jl) Experience