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work directly with the program lead, Prof Rose McCab, Dr Alexandra Bakou (Trial Manager) and Maria Long (Trial Manager) in the School for Health Sciences, City, University of London.. The post will be
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team and contribute to a programme of work led by Prof Pratik Choudhary around type 1 diabetes and technology. The appointed individual will have the opportunity to contribute to the real-world evidence
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provide support to the PI (Asst. Prof. Kean J. HSU) and other project team members on overall research administration for the projects, including coordination of research staff and trainees based on a lab
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directly with the program lead, Prof Rose McCab, Dr Alexandra Bakou (Trial Manager) and Maria Long (Trial Manager) in the School for Health Sciences, City, University of London.. The post will be based
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candidate may be employed at Grade E or Grade F depending on qualifications. The project is led by Prof. David Crundall. You will work with a small team to help create and validate our training course, and
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for motion control, and monitoring sensors. Job Requirements BS in Electrical and Electronic Engineering, Mechanical Engineering, computer engineering, or related field 4-year research experience in related
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: £38,482-£43,259 per annum, including London Weighting Allowance Job ID: 118787 Close Date: 22-Jul-2025 Contact Person: Prof Catherine Evans Contact Details: Catherine.evans@kcl.ac.uk
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Prof. John Cryan, with APC Microbiome Ireland, which addresses the communication between the brain and the gut, and how it can be influenced by the gastrointestinal microbiota. We aim to investigate
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 months ago
. Duties/Responsibilities Analysis (50%) Develop machine learning algorithms to analyze ground magnetic field perturbations Analyze the results using machine learning interpretability techniques
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Analysis and apply today! This work will advance novel research focused on sensor-based in-situ process monitoring, data correlation to end part quality, data driven machine parameterization, and data