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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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practical applications of advanced machine learning techniques. Emphasis will be given to theoretical approaches in machine learning for real-world applications, with a preferred focus on optimization, data
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Research Institute at VTC (FBRI - https://fbri.vtc.vt.edu/ ) for a tenured or tenure-track faculty position at the associate or full professor level. The PRC initiative has received substantial funding
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License No If yes, what is the required licensure/certification? Required Computer Applications: Microsoft Excel, Microsoft Word, Microsoft PowerPoint, Microsoft Outlook Required Other Computer Applications
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This research focuses on developing and validating Big Data-driven machine
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, computational statistics, machine learning, and AI. Oversee and encourage curricular innovation in undergraduate and graduate programs including FIU’s newer offerings such as the Mathematical Data Science major
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equations, statistics, game theory, machine learning Deadline for submitting applications: 20 February 2026 Required documents All documents must be submitted via the online platform https://jobs.uw.edu.pl/en
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an allied field. An MSc degree in a relevant area is desirable though not necessary. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning
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) extremes, preventive methods for mitigation of marine-induced hazards, application of machine learning techniques and opportunities provided by AI. Even though the listed advanced topics are mostly at the
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- Maintain files (creating, updating, and organizing). - Student Assistant will perform other duties and responsibilities as assigned by overseeing Faculty. Minimum Qualifications: Ability to learn and perform