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or more of the following areas: AI and machine learning, natural language processing, large language models (LLM), experience in designing prompts, fine-tuning LLMs, or distributed systems. Good knowledge
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of senior researchers, the individual will help apply machine learning methods, with a focus on reinforcement learning, to mathematical problem solving. The role emphasizes hands-on experimentation
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, energy consumption, and packet loss. The use of distributed machine learning provides a relevant solution to mitigate the lack of communication reliability [3][4]. This PhD proposes to guide the learning
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collaboration with Dr Whelan and the PhD students, machine learning tools for the handling of the Mauve and MUSE datasets. They will also be expected to lead the research into innovative ways in which the machine
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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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Application Restrictions Open to both Internal and external Job Type Open Learning Faculty Member Posting In effect from 19/3/2026 Closing Application Date 26/3/2026 OLFM Type Regular Continuous
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following areas: Strong foundation in machine learning, optimization, and deep learning algorithms, including Transformer architectures. Hands-on experience or solid theoretical knowledge of LLMs/SLMs
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thesis is not pre-defined and should be defined by the candidate over the course of the first year. The domain of the PhD thesis must be machine learning and either control theory, path planning, or multi
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Materials Required: Further Info: https://argonne.wd1.myworkdayjobs.com/Argonne_Careers/job/Lemont-IL-USA/Postdoctoral-Research-Associate---Machine-Learning-in-High-Energy-Physics-Detector-Operations_421270
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Duties Teach any of the following postgraduate course(s) in the upcoming Semester A 2024/25 and/or Semester B 2024/25: Statistical Machine Learning I Statistical Machine Learning II Exploratory Date