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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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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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developing image analysis and machine learning algorithms and tools for aerial imaging and analysis. You will also contribute to data collection, data curation, and the development of a data portal for project
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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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learning algorithm to analyze how experimental parameters ( 3D printing and electrospinning) affect the design. At least 3 semesters of FIU work experience or related experience outside the University with
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engine. Algorithm Development: Contribute to designing, prototyping, and testing algorithmic models for personalized content recommendations. System Evaluation: Support the evaluation of the recommendation
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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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for engineering-driven AI innovation. Ideal candidates will have: (1) A PhD in Management Science and Engineering, Computer Science, or a related discipline, with a focus on AI/ML theory, algorithms