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focus on research and development in Atmospheric Pressure Matrix-Assisted Laser Desorption/Ionization (AP-MALDI) mass spectrometry and molecular imaging, using high-resolution Orbitrap MS instrumentation
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spatial omics datasets. The position will also contribute to multi-modal data integration efforts that combine imaging, genomics, and machine learning approaches. Key Responsibilities Data Processing
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image sequences. As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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Position Description The Unsteady Flow Diagnostics Laboratory (UNFoLD) led by Prof. Karen Mulleners at EPFL in Lausanne is looking for multiple PhD students to join the group in the fall of 2025 or early
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
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complete picture of fish habitat use and connectivity. The PhD is part of the section for Ecosystem based Marine Management and the Marine Habitats research group, as well as several synergistic initiatives
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Pajcini, Ph.D. in the Department of Pharmacology and Regenerative Medicine at the University of Illinois in Chicago. The lab studies the processes that lead to the development and differentiation
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will include: 1. Implementing and quality-assuring MR Fingerprinting scans on multiple clinical scanners 2. Integrating advanced imaging tools for image processing and analysis. 3. Coordinating closely
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At the Faculty of Engineering and Science, Department of Materials and Production a position as PhD stipend in Muscle Neuromechanics and Ultrasound Imaging, within the doctoral programme Materials