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Proven experience with deep learning frameworks such as PyTorch, and familiarity with multimodal data fusion is highly desirable Ability to work independently, as well as collaboratively in
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AI, Biomedical Informatics, Computational Biology, or a related field Strong programming skills in Python and modern ML frameworks Experience with deep learning and large language models Strong
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data and multimodal datasets combining imaging and molecular measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with
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records and medical images, for applications pertaining to patient diagnostics and prognostics. We are seeking a Postdoctoral Researcher to join the team and make significant contributions to the field
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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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learning and deep learning models for trait prediction and climate-resilient wheat breeding. Analyze time-series UAV data using crop models in combination with genomic and agronomic information. Collaborate
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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have
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. We are seeking a Postdoctoral Researcher to join the team and make significant contributions to the field. The researcher is expected to have (i) strong machine learning skills to improve model
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. Apply deep learning approaches to support optimization of segmentation methods for clinical neuroimaging datasets. Investigate developmental differences in infant brain functional networks. Support
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analysis packages, basic shell scripting, experience in Unix/Linux platform) and experiences with deep learning tools (e.g., PyTorch, TensorFLow, Keras), neuroimaging analysis tools (e.g., PMOD, SPM, FSL