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decisions. Adheres to University and unit-level policies and procedures and safeguards University assets. Develop various machine learning and data mining models including deep convolutional neural networks
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genetic basis of plant–microbe interactions, with a particular emphasis on data integration across plant species and data types (genomics, transcriptomics). Design, adapt and use deep learning methods
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Schemes of Service: Faculty Division: Business, Communication and Design Employment Type: Fixed Term At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical
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calculations Machine Learning/Deep Learning techniques. Education and Experience: A PhD in physics, astronomy, or a closely related field must be completed before the position begins. Additional information
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consequently more heat flux from the relatively warm, deep Arctic to the vulnerable surface sea ice. Climate models do not currently represent these processes, which are dynamically different from those
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strategies. Duties and Responsibilities Design, implement, and evaluate deep learning models for spatiotemporal data, with an emphasis on medium-scale foundation models. Leverage model embeddings in causal
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/Qualifications Strong research track record in AI and scientific applications. Excellent knowledge of Machine Learning and Deep Learning. Strong Python programming skills. Experience with PyTorch, TensorFlow
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docking to investigate viral spike/capsid architecture, thermal stability, and immune epitope accessibility. AI/Deep Learning: ML/DL model development (e.g., PyTorch, Lightning) for predicting antigenicity
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IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences) | Czech | 2 months ago
-scale deep learning, ideally applied to protein or nucleic acid sequences Ability to work independently and to translate diverse scientific use cases (brought by wet-lab and computational colleagues alike
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Researcher will work in Professor Benjamin Peherstorfer’s group (https://cims.nyu.edu/~pehersto/ ) on scientific machine learning at the Courant Institute of Mathematical Sciences where they will help