8 parallel-processing-bioinformatics Fellowship positions at University of Leeds in United Kingdom
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hydrological models to improve malaria transmission estimates’ funded by the UKRI Natural Environment Research Council (NERC). The project aims to embed hydrological processes in models of malaria transmission
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underpinning research. As MSCA PhD Fellow (DC2) in Leeds, you will investigate how molecular self-assembly governs the ultrastructure of PNNs. PNNs play a pivotal role in regulating neuroplasticity, a process
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online process analytical technology (PAT), embedding sustainability metrics into the optimisation loop, and apply transfer learning to accelerate the transition from batch to continuous flow processes
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Are you an ambitious researcher looking for a career defining challenge? Do you have experience in modelling real systems and complex processes? Are you involved in impact-carrying research focused
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of using models and observations to study weather and climate processes. You will have knowledge of atmospheric dynamics. You will have evidence of a strong commitment to publishing scientific results
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mapping tools such as Google Earth Engine or Microsoft Planetary Computer, and it is likely that developments such as satellite data embeddings and GeoAI will offer potential for increasing the accuracy and
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process in a disease-relevant model in real time. This involves developing cutting edge in vitro and in vivo models that will enable us to identify new targets and optimise existing treatments
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tailored to your career goals. You will have, or be close to obtaining, a PhD in deep learning, computational geosciences, computer sciences, mathematics, or physics, and have experience of developing and