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Field
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, binding, specificity, stability, and catalytic efficiency of proteins of interest. Data generated will be used to develop large databases for use in the evaluation of protein function prediction algorithms
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using deep learning, computational chemistry, medicinal chemistry, chemical biology, and molecular cell biology to develop novel therapeutics to tackle complex diseases such as cancers. Successful
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detailed design at all levels to cover the range of BEMS as operated by the University. • Highly developed and demonstrated consultative, interpersonal and communication skills • Evidence of ability
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of existing applications to meet specific scientific project needs; support the development of data models, databases or software applications; produce, present and discuss high quality data analysis reports
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new code in python at PEP8 standards for solving problems toward creating neural connectome maps). Algorithm development initially will involve solving problems such as: (1) base calling of in situ
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figures of lab members. Candidate will train on the lab’s fundamental algorithms and run them in a collaborative manner with other team members to generate paper figures and make discoveries. Collaborative
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apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and Materials Theory division, a
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in an interdisciplinary and collaborative team to pursue research in degraded visual environment mitigation. The primary duties of this position will be to research and develop algorithms, prepare
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with emerging neuroscience evidence that synapses perform nonlinear transformations rather than merely transmitting signals. This project aims to develop and analyse local learning rules for KANs
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well as participating in collaborative projects with other lab members and developing experimental protocols and experimental cell and molecular biology standards for the laboratory. The scientist will work on projects