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estimation with a large (20 million obs.) dataset and (2) experience in programming matlab to run economic model simulations. Knowledge of trade and open macro literature and cutting-edge models used in recent
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of large-scale high-throughput genomic data sets. Optimally, this will include genome-wide association studies, and/or exome or whole genome sequencing analyses. Alternatively, you will have experience in
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of novel machine learning methods to analyse and interpret large-scale multimodal data using samples primarily derived from large clinical trials and studies. The role will also involve working closely with
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work on large-scale understanding of coastal wetlands - primarily mangrove forests and tidal marshes. This will include mapping and modelling of distribution, value, condition, and opportunities
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Assistants is £32,546 - £35,116 and for Research Associates this is £37,174 - £45,413 per annum. Suitable candidates should have previous experience of genetic analysis of large scale genome sequence data and
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across CG-TIC to process and analyse complex and varied datasets. What you will do The collaboration will generate and have access to clinical and immunological data as well as many large data sets
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the team, including our training courses (https://science.ai.cam.ac.uk/resources ), study groups and lecture courses such as Machine Learning and the Physical World and Advanced Data Science (https
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pension scheme, health cash plan, life assurance, employee assistance programme, free on-site parking, free use of gym and swimming pool, free lunch plus other benefits commensurate with working for a large
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interpersonal skills are required to ensure success in liaising with a large and diverse research team: Ph.D. (or be about to obtain) in Organic Chemistry. Strong background in synthetic organic chemistry
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for the administration of a range of events, from regular weekly catering services and bookings to the delivery of large, complex events run throughout the year. You will be responsible for a series of administrative and