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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning for improving
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describing the effect of conditions on stability. Testing the model in standard stirred tank apparatus Refining the model to allow predictability between different types of apparatus. Defining an algorithm
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the Generative Flow Network (GFlowNet) algorithm. We plan to further enhance this algorithm to consider the shape of biological binding sites and incorporate modules for optimizing physicochemical properties
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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and decoding information from neurons Prior experience dealing with custom hardware, FPGAs, and using/writing APIs to communicate with the hardware Like to live in the intersection of biology, hardware
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of biological databases, algorithms and pipelines; experience in working with phylogenetic/ genomic/transcriptomic/systems biology tools will be a bonus; being well organized, eager to learn and ready to
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degree in the field of bioinformatics and computational biology. Work plan: To develop and evaluate a hybrid quantum–classical approach for NGS data alignment, combining Grover’s algorithm with classical
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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our group, you get the opportunity to use the latest algorithms in machine learning for improving
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Job reference: BMH-030198 Salary: £37,694 - £41,064 per annum, depending on relevant experience Faculty/Organisational Unit: Biology, Medicine Health Location: Oglesby Cancer Research Building, 555
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or incomplete. Information Your tasks will include: Developing and benchmarking ML/AI algorithms tailored to low-data regimes — e.g. few-shot learning, transfer learning or data-efficient representation learning