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. This group uses state-of-the-art Earth observation data and advanced computer techniques to study the Polar regions. We specialise in using Synthetic Aperture Radar (SAR) and altimetry satellite data
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approaches, machine learning) where appropriate. The successful candidate will actively promote FAIR data practices and will have opportunities to contribute to teaching, training, and wider community
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the industry to lead and/or conduct innovative research on, but not limited to evolutionary computing, job scheduling, transfer optimization, transfer learning, reinforcement learning, large-scale
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Requirements: A PhD degree in mathematics or related areas, with a strong background in topological data analysis (TDA) and machine learning on biomolecular data Proficiency in programming languages such as
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to most destinations in the world. Interested candidates are encouraged to send a brief cover letter, CV and the names and contact information of 3 references to: Prithu Sundd, PhD - psundd@versiti.org
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) GRADE 7, £39,355 - £45,413 pa Fixed-term Ref: 095593 A Research Fellow position is available in the group of Professor M. J. Rosseinsky OBE FRS to work in a team of computer scientists and materials
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ethical and security standards. Concept and Algorithm Development: Innovate in data science, machine learning, and AI. Data Analysis and Reporting: Contribute to data analysis, reporting, and publication
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at the Institute of Genetics and Cancer. Informal enquiries may be directed to Dr Athina Spiliopoulou (A.Spiliopoulou@ed.ac.uk ). Your skills and attributes for success: PhD in machine learning, genetic epidemiology
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of the following areas will be a merit. Advanced AI methods development in Python or any other relevant programming language Computer Vision and image analysis Handling of large dataset Qualifications Applicants
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. The role will focus on developing machine learning and mathematical optimization solutions for electric vehicle fleet charging optimization under different constraints. Key Responsibilities: Formulate