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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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using Multimodal AI models as per the preference of the student. What you bring to the table PyTorch, Multimodal AI, Gaussian-Splatting, Image Processing (AI Approach). OR Experience with loading and
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on microscopes Experience with data analysis (in particular image analysis) in a programming language (ideally Python) Experience with image processing software (e.g. ImageJ, Imaris, Arivis, Amira) Experience with
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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Master Thesis - Development of ligand conjugated lipid nanoparticles for targeted T cell delivery...
biological samples' 3D structure and molecular identity. At iBIO, we bring together cutting-edge science from biology, chemistry, engineering, and computer applications. Our overarching aim is to obtain a
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pursuing a Bachelors or Masters degree in engineering, physics, mathematics or computer sciences and related discipline and/or an unaffiliated recent graduate with a Bachelor/Master degree from
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
Job Code: 18-25 Job Offer from June 04, 2025 The Department of Prof. Dr. Stefan W. Hell invites applications for a PhD position exploring AI approaches in optical science, molecular imaging and
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application-inspired. In our Department System Process Engineering, we are seeking for a Post Doc (m/f/d) – 100 % in non-invasive measurement methods for process and quality control During agricultural-related
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In the Phytophotonics department, you will work as part of an interdisciplinary team at the interface between plant sciences and optical technologies. The focus is on various spectroscopic and imaging
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transfer. Its current five-year scientific programme, Molecules to Ecosystems (2022–2026), aims to deepen our understanding of life — from molecular mechanisms to complex ecosystems — with a strong emphasis