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Field
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position is available on the development of geographic information systems methodology and spatiotemporal modelling for climate-sensitive infectious disease forecasting. The work will contribute to ongoing
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in the relevant discipline area, such as computational/theoretical physics or chemistry, or applied mathematics. Demonstrated evidence of computational modelling experience, including code development
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large data set? We are offering a unique opportunity to drive the development, capture and iterative improvement of both a large data set model, and the techniques to generate informative report-based
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electrophysiology (single-unit, multi-unit, or related approaches) in animal models. Strong technical skills in setting up and troubleshooting complex experimental systems. Proficiency in programming and data
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joint multi-state models for health care processes and disease progression”. The central aim of this 36 month project is to develop new methods for the joint modelling of disease or other healthcare
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language models. Our main goal is to create a PL+AI system that is the best at verified program synthesis. We will use the verification-aware programming language Dafny and co-evolve an LLM and a discovery
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. This is primarily for an NIH-funded project developing multimodal variational autoencoder models and probabilistic trajectory analyses for latent spaces formed from neural, genetic, and behavioral data
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applied mathematics. Demonstrated evidence of computational modelling experience, including code development and data analysis. Ideally experience using one or more of the following: Molecular dynamics
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highly accurate and efficient computational model by integrating the newly developed approaches into the numerical program developed in the ‘OceanCoupling ’ project. We would like the successful applicant
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Documented experience in at least one of the following areas: molecular cloning and mutagenesis in non-model bacterial species (ideally in a BSL-2 environment), mass spectrometry (ideally in combination with