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to the advancement of AI applications in biological sciences. This role presents a unique opportunity to work with pangenomic datasets while exploring the application of Large Language Models (LLMs) and machine
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novel and advanced statistical methods such as in AI, and machine learning is also highly desired. For an informal discussion about the position please contact Professor Georgina Jones: g.l.jones
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AI/machine learning, and data analysis using MATLAB or Python. Provide technical assistance on related research projects, such as preparing progress presentations and reports for funding agencies
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 21 hours ago
.) Departmental Preferred Experience, Skills, Training/Education: Ph.D. in design-related discipline, specializing in deep learning and biometrics. A strong background with evidence of experimental and AI/machine
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diffusion models using path integral formulations. This project aims to advance quantum machine learning by: Designing a quantum counterpart of diffusion models; Leveraging path integral methods to model
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are essential. Preferred Qualifications: Prior experience with machine learning (ML) in high-energy physics is highly desirable, though not required. Appointment Details: The position is expected to be based
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Large Language Models Natural Language Processing (NLP) Deep Reinforcement Learning Theoretical Foundations of Deep Learning and AI Optimization Techniques in Machine Learning Collaboration and Mentorship
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, written, and oral communication skills in English. Exhibit strong organisational skills and the ability to meet deadlines and complete projects. Have expertise in machine learning and/or programming (highly
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Are you keen to pioneer machine learning models that address the challenges of robot perception? We are recruiting a research fellow who will work on our EPSRC-funded research project on “Active
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School of Engineering and Applied Sciences at Harvard University invites applications for a postdoctoral position in robot learning, beginning in September 2025, or soon thereafter. The position is for one