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and the seventh century CE: https://www.nottingham.ac.uk/news/research-on-early-british-voices-and-identities. This project will use datasets previously curated by team members which will be
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publications, conference presentations, and robust coding practices, including version control and reproducible data pipelines. Proficiency in Python, ML frameworks such as TensorFlow or PyTorch, statistical
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conducting research using large-scale routine or registry data, preferably in cancer. High-level proficiency / experience developing reusable analytical pipelines or modular code (in R, Stata, or Python) with
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collection. Can demonstrate proficiency in R or Python of data handling and visualisation. Has understanding of marine food web dynamics and trophic models alongside strong quantitative and analytical skills
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or machine learning. Excellent programming skills in Python and deep learning frameworks A collaborative mindset and interest in socially impactful research. Experience with sign language data, multimodal
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-dimensional visual stimuli (https://doi.org/10.1101/2024.09.27.615442), and how the inputs onto single depth-selective neurons give rise to their response properties. To accomplish this, this project, which you
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a full job description please visit UCL’s online recruitment portal (https://www.ucl.ac.uk/work-at-ucl/search-ucl-jobs ) and search using vacancy reference B02-10144. To apply, please upload a current
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methodologies. Applicants must demonstrate strong programming skills in at least one scripting or programming language (e.g. Python, R, Perl, Nextflow, C++, or Java) and experience in areas such as database
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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the challenges posed by extrachromosomal DNA in cancer. Supported by Cancer Grand Challenges, a global initiative addressing key issues in cancer research, it is funded by CRUK and the NIH (https