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About the Role This is an opportunity to work as part of the team and project “Accelerating charged particles in space” funded by a Royal Society URF led by Dr Heli Hietala. The postdoc project
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” which examines signal processing and machine learning methods for inferring active travel activities from optical fibre signals. About You Applicants must have an Undergraduate Degree in Computer Science
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the areas: AI, deep neural networks, machine learning, applied topology, probability, statistics, signal processing. About the School The School has an exceptionally strong research presence across
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et al, Leukemia 2018; Poynton et al, Blood Adv 2023; Coulter et al, J Mol Diagn 2024). The wet lab/computational biology postdoc will lead a project investigating residual follicular lymphoma cell
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This is the expected starting salary for this post however appointment at a higher point may be made for candidates who demonstrate exceptional skills and experience relevant to the role. Right
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techniques like Raman spectroscopy, AFM, SEM, XPS, and electrical measurements such as Hall effect, four-point probe, and current-voltage (I-V) testing. A proven track record of high-quality research
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-scale data analysis you will be able to demonstrate your expertise in using R and Python to process and analyse genomic data and to employ learning frameworks. Appointment is at either a grade 4 or grade
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Institute, a pioneering biomedical research institute in London where our wet lab is located. We are also part of Cancer Research UK City of London Centre, which sponsor our high-performance computer cluster
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well as qualitative approaches including semi-structured interviews with women, families, and clinicians. These interviews will inform the design process and deepen understanding of the everyday contexts and
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defending the cultural value of knowledge for its own sake. You will also possess computational expertise in data mining and / or analysis, ideally including language processing, and be able to work with an