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Field
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applications, including solving mathematical reasoning problems and tackling the Abstraction and Reasoning Corpus (ARC) challenge among others. The ideal candidate has a strong background in machine learning and
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Your profile PhD applicants must possess a Master's degree in mathematics, theoretical physics, or computer science. Candidates should have an exceptional academic record and a robust mathematical foundation. Candidates are also expected to have strong coding and implementation skills, with the...
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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17 Sep 2025 Job Information Organisation/Company Graz University of Technology Department Institute of Machine Learning and Neural Computation Research Field Computer science Researcher Profile
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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both sites. The project sits at the interface of cell line engineering, protein science and machine learning and you will receive advanced training in these areas while developing methods to accelerate
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about the intersection of computational science, machine learning