88 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" research jobs in Sweden
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that support the unit for area protection and marine spatial planning, as well as operations at SLU Aqua. Your profile You have documented expertise in marine ecology and computer vision and machine learning
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will (micro-)benchmark Java-based applications using JMH. You will collect performance measurements from real projects, statistically analyse them, and conduct experiments with modern machine learning
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scientific curiosity Mastery of data visualization and scientific communication Extensive knowledge of relevant machine learning and AI techniques Self-motivated individual with ability to work independently
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-Geometric Foundations of Deep Learning or Computer Vision KTH Royal Institute of Technology, School of Engineering Sciences Job description The Department of Mathematics at KTH welcomes applications for a
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/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We focus on data-driven models for complex and temporal data
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into mechanosensory corpuscles (Nikolaev et al., Sci Adv 2020; Nikolaev & Ziolkowski et al., Sci Adv 2023; Ziolkowski & Nikolaev et al., Sci Adv 2025). This is just the beginning and there is still much to be learned
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Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may
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. Your profile You have documented expertise in marine ecology and computer vision and machine learning methods for video-based fish monitoring. You have excellent IT skills and experience in handling
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software related to the medical field Experience of specific software and programming languages, specifically ones suitable for machine learning, e.g. PyTorch or TensorFlow. Strong ability in spoken and
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machine learning models in simple, standalone devices that are capable of advanced processing. Building on our work on solution-based neuromorphic classifiers (https://doi.org/10.1002/advs.202207023