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Field
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application of machine and deep learning models. The balance between experimental and computational method development will depend on the candidates’ profiles. Start date is expected to be 1 June 2026 or as
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dissemination, and translational opportunities Job Requirements: PhD in Chemistry with a focus on computational/peptide/organic/machine learning or a closely related discipline At least one first-author
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, as well as from industry. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/294560/phd-research-fellow-in-deep-learning-for-medical-imaging-and-multi-modal-data-in
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or electrochemical system PhD in Chemistry/Materials Science/Physics Encourage initiating activities on MOF development, devising, and analytical process Experience in machine learning will be preferred Good oral and
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computational electromagnetics and electromagnetic simulation techniques. Experience in AI-based RF transistor modelling is highly desirable. Solid knowledge of machine learning algorithms and their application
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computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability to communicate scientific results clearly through
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Research Infrastructure? No Offer Description Based at Australian Institute Machine Learning (AMIL), City East Campus 2 x Full-time, 2-year fixed term contracts Salary Range: $114,917 - $135,932 per annum
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researchers and PhD students. The research groups conduct research in various areas of mobile network systems, multimedia and AR/VR/XR systems, robotics and machine learning, focusing on fundamental aspects as
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focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute
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/job/295231/phd-research-fellow-in-machine-learning-and-statistics Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/295231/phd-research-fellow-in-ma… Requirements Research