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project is to develop a series of surrogate models focusing notably on Physics-Informed Neural Networks to emulate the process of sediment deposition, diagenesis, and potentially fracturing, working closely
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Experience in devising and developing novel machine learning algorithms Hands on experience with ROS and physical robots Excellent mathematics skills, particularly in areas relevant to robotics and AI
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at each stage of the recruitment process. We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community
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) that combines a mix of remote and regular on-campus working. Your skills and attributes for success: Essential PhD (or near completion) in Computer Science, Physics, Mathematics, or related field
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extended.) Person Specification Essential Criteria: Qualifications A good first degree in Mathematics, Physics or a related subject. A PhD (or be close to submission) in Applied Mathematics, Solar Physics
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-disciplinary research environment Desirable criteria 1. Experience in devising and developing novel machine learning algorithms 2. Hands on experience with ROS and physical robots 3. Excellent
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the application process, please contact: mailbox-hr@cruk.cam.ac.uk . Please quote reference SW46580 on your application and in any correspondence about this vacancy. The University actively supports equality
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About us The Department of Geography is a vibrant community of students, teachers and researchers. Our holistic approach encompasses both human and physical geography perspectives on global
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diversity. Application Process You will be required to upload an up-to-date CV and a supporting statement as part of your online application. Your supporting statement must clearly demonstrate how you meet
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at claire.kennan@rhul.ac.uk . For queries on the application process the Human Resources Department can be contacted by email at: recruitment@rhul.ac.uk Please quote the reference: 0725-153 Closing Date: 23:59, 1