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, we need an imaging scheme that captures relevant features at different length scales and integrates them into a single reconstruction volume. This PhD project focuses on learning-based phase retrieval
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application! We are now looking for a PhD student in Computer Vision and Learning Systems at the Department of Electrical Engineering (ISY). Your work assignments Your task will be to analyse and adapt vision
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quantitative shape representations Analysis of structure–function relationships between morphology and movement Modelling genome–phenotype relationships using machine learning and genomic language models
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, they will take an active role in designing and commissioning a pioneering Self‑Driving Lab, a next‑generation autonomous research platform that will integrate Machine Learning and Bayesian optimization
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is linked to the ELLIIT project New Machine-Learning Methods for High-Dimensional, Population-Scale Health Data , conducted in collaboration with Lund University. The project aims to develop and apply
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AI hardware beyond traditional computing architectures. Gain a unique combination of skills in mathematics, machine learning, and photonics. Be part of a multidisciplinary research team spanning
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increasingly rely on data-driven models to extract, represent, and interpret information from complex and evolving environments. Traditional machine learning approaches, as well as many classical signal
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biomedical engineering, electrical engineering, machine learning, statistics, computer science, or a related area considered relevant for the research topic, or completed courses with a minimum of 240 credits
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(e.g. computer vision, deep learning, AI) and green life sciences (e.g., remote sensing, crop modelling, and food security), within the European funded project AgriscienceFM (Horizon programme), which
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representations Analysis of structure–function relationships between morphology and movement Modelling genome–phenotype relationships using machine learning and genomic language models The project offers a unique