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The Machine Learning for Health team at the Institute for Molecular Medicine Finland (FIMM) , University of Helsinki, is currently seeking a highly-motivated postdoctoral researcher to join our team
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multidisciplinary team members and the broader scientific community. Contribute to a culture of innovation, collaboration, and continuous learning. Support Research Excellence Adhere to all institutional requirements
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compliance (5%). •Conduct research on artificial intelligence (AI) and machine learning (ML) to analyze large-scale biological, genomic, metabolomic, and phenotypic dataset (25%). •Investigate the genetic
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at NeuroSpin is very scientifically stimulating, combining MRI physicists, machine learning experts, and cognitive neuroscientists. Team members go there to collect data and collaborate with their colleagues in
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). Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Knowledge of basic molecular biology
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: A doctorate in a Machine-Learning related field A deep knowledge of Control Theory, both classical and deep learning based A solid publication record in top level ML venues such as NeurIPs, ICML, and
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or machine learning is highly desirable Prior experience with liquid biopsy work is welcome but not required Proven ability to think creatively, work collaboratively, and communicate effectively Fluency in
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(AI) and machine learning (ML) methodologies. The position involves annotating clinical data, collaborating with AI/ML/NLP teams, developing algorithms, and generating insights to improve patient care
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engineering and clinical physiology. Projects may involve signal quality assessment, artifact detection, waveform segmentation, feature extraction, hemodynamic modeling, time-series analysis, machine learning
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National Aeronautics and Space Administration (NASA) | Merritt Island, Florida | United States | about 17 hours ago
or machine learning applied to plant traits. Candidates with strong quantitative skills, interest in interdisciplinary collaboration, and motivation to explore crop performance in novel environments may find