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breakthrough and to contribute to the welfare of society and humanity through developing innovative technologies. We also conduct research on ethical, legal and social issues caused by the spread of AI
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application. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy
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/or observationally motivated model-building for SMBH feeding and feedback. The group integrates observations, theory, data analysis, algorithm development, model-building, and numerical simulations
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sparse algorithms. The successful candidate will contribute to advancing secure, trustworthy, and efficient AI solutions for scientific applications. Key responsibilities include developing state
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metagenomics assembly” funded by the Research Council of Finland in the research group of University Lecturer Leena Salmela. We develop models, algorithms and data structures for high throughput sequencing data
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for biomarkers in 7T images. - Development of artificial intelligence algorithms and models for the processing and analysis of MRI images/spectra, focusing on the detection of tumor tissue and the quantification
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/Statistics, Medical/Health Informatics. Strong computational and programming skills with abilities to develop cutting-edge large-scale machine/deep learning algorithms using high-performance computing (HPC
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, complex systems. Strong communication and writing skills; ability to work both independently and as part of a team. About the team The DATA team develops foundational mathematical and algorithmic approaches
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associate will conduct theoretical studies and numerical simulations, develop new methods and algorithms, and mentoring junior group members. Physical Demands and Working Conditions Physical Activities
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with