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use of supervised fine tuning of a pre-trained vision transformer, U-Net architecture, or related topic. Projects in computer vision for microscopy image analysis are especially relevant. Include a link
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Job Purpose To make a leading contribution to an exciting new UKRI funded project to develop ‘Ultrasound-Guided Activation and Imaging of Engineered Bacteria for Stroma Reprogramming’, working with
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, the student will apply drone imaging, AI analytics, and simulation tools to support more sustainable and circular agriculture. They will collaborate with farmers, engineers, and policy experts to create
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science » Computer systems Computer science » Modelling tools Computer science » Informatics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 May 2026 - 23:00 (Europe/Paris
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deadlines. • Ability to work independently, and to be an accomplished team player. Preferred Qualifications • MS or PhD in chemistry, physics, materials science, engineering, or a related physical science or
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the deadline may be considered. To apply: please click the Apply Now icon on this page or visit Faculty Lecturer Positions or https://careers.calstatela.edu . Please address all questions to the department
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received after the deadline may be considered. To apply: please click the Apply Now icon on this page or visit Faculty Lecturer Positions or https://careers.calstatela.edu . Please address all questions
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | about 1 month ago
, including soil organic matter analyses and 3D image processing. - Programming skills in R or Python to automate image analysis, build a classification, with the aim of making the reference framework
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State University of New York University at Albany | Albany, New York | United States | about 15 hours ago
, AI, and quantum information processing. Requirements: Minimum Qualifications: A terminal doctoral degree (PhD or equivalent) in physics, computer engineering, or related field from a college or
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Python, PyTorch, and Linux/command line Familiarity with LLM in-context learning and prompt engineering Basic understanding of modern LLM models, ecosystems, and pipelines, including retrieval-augmented