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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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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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that there will be collaboration with different stakeholders in industry and regulators during the project, and the candidate can expect a stay abroad during the PhD project. The PhD student will be a part of the
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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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, 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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effect on bulk functionality. In this PhD project, we dig deeper to obtain a better molecular understanding of the effects from different extraction methods. To accommodate this, we will explore protein
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asynchronous AI-led chemical optimisation across chemistry laboratories¿. This role sits at the intersection of robotics, machine learning, and chemistry, aiming to develop robotic systems that work
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hemocompatible coating strategies to improve membrane–blood interactions. - Model and optimize membrane performance using computational tools, machine learning, and artificial intelligence Work Plan - Synthesis
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with fabrication engineers to translate physical processes into machine learning models, design and train deep learning architectures, and evaluate their ability to generalise across different process
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position The PhD student will: Develop machine learning models for digital phenotyping and genomics Work with multimodal datasets (images, 3D data, motion, genomics) Implement models in Python (e.g. PyTorch