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learning, or optimization Strong programming skills in Python and experience with scientific computing and machine-learning libraries Ability to work across experimental, robotic, and computational systems
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Researcher in The School of Chemistry. The InTeleCat project involves the use of machine learning and AI as applied to organic synthesis. It is a large collaborative project involving researchers in the US
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: This project, which is part of the EPSRC progarmme grant on Quantum advnatage in Quantiative Quantum Simulation (QQQS), will involve adapting and using our existing ultracold erbium and potassium machine
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methylation, chromatin accessibility), and clinical data. · Develop, apply, and benchmark machine learning and statistical models for subtype discovery, classification, and outcome prediction. · Contribute
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://sandrasiby.github.io/ . The lab website can be found at https://sites.google.com/nyu.edu/haven-lab The successful candidate will engage in research that includes applied machine learning, systems building, and Internet
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Finance at EPFL seeks postdocs to reinforce our research in quantitative finance with a focus on applied machine learning. Main duties and responsibilities Working and collaborating on research projects
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enable students to earn associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build
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4 Aug 2026 Job Information Organisation/Company Technological University Dublin Department Human Resources Research Field Technology » Computer technology Researcher Profile Recognised Researcher
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Intelligence and Machine Learning, Computational Statistics, Random Matrices, Free Probability, Stochastic Control, Mathematical Finance, Stochastic Partial Differential Equations, Markov Processes, Branching
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candidates with expertise in areas such as: Construction Informatics Digital Engineering BIM and Digital Twins Artificial Intelligence and Machine Learning Automation and Intelligent Systems Smart