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As a postdoctoral researcher, your primary responsibilities will be: Develop machine learning and deep learning models, with a strong focus on computer vision, for the characterisation and
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against simpler machine-learning baselines; • train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies and
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that prioritise student learning in the age of AI. Job requirements You hold a PhD in Educational Science, Learning Sciences, Social and Behavioural Sciences, Engineering Education, Human-Computer Interaction or a
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and/or the analysis and processing of sensor data, for example building and deploying sensing systems (wearable, ambient, RF, distributed), edge and on-device data processing and machine learning
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compositionally complex recycled steels, using density functional theory and machine-learned interatomic potentials, in close collaboration with leading academic partners and Tata Steel. Job description At TU Delft
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experience with empirical research and a strong aptitude for quantitative and technical methods. Experience & competencies Experience with Python and machine learning, preferably applied to medical imaging
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microstructure in materials. A distinctive element of the project is its data-driven approach. Together with colleagues at Saxion University of Applied Sciences, you will contribute to the development of machine
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their added value against simpler machine-learning baselines; train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies
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systems and control theory, circuit theory, optimization, and machine learning, with the ultimate goal of advancing the mathematical foundations of physics-based learning. Your responsibilities include
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decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch energy