51 algorithm-development-"Multiple"-"Simons-Foundation" "Prof" Fellowship positions at University of Birmingham
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Summary A 3 year Bone Cancer Research Trist/GOSH funded Research Fellow post, starting October, is available within the lab of Prof. Clare Davies and Dr. Susanne Gatz investigating synthetic lethal
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prototypes. Top-down 4D characterisation of enamel structural evolution using macro- using multiple techniques at macro-, micro- and nano- scale resolution in macro- and micro-fluidics setups to observe enamel
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machine learning. Supervision will be provided by Prof. Ali Mazaheri, as well as Prof. Fang Gao Smith, and Prof. Helen McGettrick. The successful candidate will have a strong background in psychology
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inversion techniques and signal processing. Strong programming skills, Proficiency in scientific computing (e.g. Python, MATLAB, or similar) for algorithm development and data handling. Experience with sensor
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the topical area of Quantum-enabled radar at UoB through contributions to securing research inputs and outputs Contribute to the management and delivery of the programme Lead efforts on the further development
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development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning algorithms might support the wider integration of, and uptake
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. Develop research objectives and proposals for own or joint research, in the area of interest of the hosting laboratory (Prof. T. Carlomagno) Contribute to writing bids for research funding Acquire, analyse
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partners. Main Duties Improve, develop, implement, and apply advanced computational tools and workflows to process, analyse, and interpret large-scale LCMS-based metabolomics datasets across multiple species
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the prevalence and risk of modern slavery. There will be a focus on Bayesian nonparametric methods and practical development of MCMC algorithms that can be applied to data. Translating the project findings
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an STFC-funded postdoctoral researcher to develop new inverse modelling (‘retrieval’) methods to extract 3D information from JWST secondary eclipse observations. The models will be applied to JWST