33 software-engineering-model-driven-engineering-phd-position PhD positions at University of Cambridge in Uk
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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
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Applications are invited for a fully funded 4-year PhD studentship based in the Department of Biochemistry, University of Cambridge, and the new AstraZeneca Discovery Centre in Cambridge
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email Ms Becky Evans (dial-admin@eng.cam.ac.uk ) to let her know their interest in this position once their PhD application has been submitted. Interviews for the studentship will be held in September
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. Applications may close early if the position is filled before this date. Please note that any offer of funding will be conditional on securing a place as a PhD student. Candidates will need to apply separately
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of cancer, namely adenocarcinoma, which was driven by a transcriptional pathway that involves Androgen Receptor (AR) and a pioneer factor called FOXA1 that helps tether AR to the chromatin. Recent new
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of the genome. This position will be primarily based in the Balasubramanian Lab in the CRUK Cambridge Institute (CRUK CI), and will involve collaborative interactions with the group's sister lab in the Yusuf
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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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and Technology (CST) at the University of Cambridge. The goal of this PhD programme is to launch one "deceptive by design" project that combines the perspectives of human-computer interaction (HCI) and
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environmental terms, this multiply-colonised and repeatedly-engineered city is built in a wetland without a significant natural harbour; 2) In social terms, in a heavily nationalised state, the city has resisted
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading