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models and metrics for fairness in decentralized environments. Develop prototype systems and perform experiments on real-world datasets and platforms. Publish research outcomes in high-quality venues and
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new research collaboration with Ames Lab focused on studying the mechanisms of biomass degradation using multimodal imaging techniques. This position will specifically focus on the use of single-walled
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following skills: Strong interest in the field of neuroimaging, psychiatry and genetics. Computer skills: Strong level in the main informatics software (FSL, Freesurfer, fMRIprep) and coding languages (R
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: PhD in CS/ML/medical informatics, strong publication record, and hands-on experience with generative models in medical imaging. Postdoctoral Research Associate (f/m/d) EU Research Project TWIN-X Full
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human and murine cells cultured in vitro and collect cancer and non-cancer tissues from mice; processing cell and tissue samples for protein- and DNA/RNA-related assays and immunohistochemical staining
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 4 hours ago
into practical tools, guidelines, and prototype implementations. Furthermore, the candidate may contribute to broader research efforts, including digital chart compilation workflows, geospatial data processing
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) learning numerical methods for wave-equation-based processing, imaging, and inversion. Wave phenomena are ubiquitous in science, and they extend to objectives ranging from global Earth discovery, to natural
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characterisation using multi-modal operando datasets. Practical experience in the design, construction, and operation of experimental setups for imaging-based investigation, of battery behaviour under in situ
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interpreting brain imaging data (e.g., FSL, SPM, AFNI) - Demonstrated ability to complete projects, as evidenced by first-author publications - Excellent organizational, interpersonal, and communication skills
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About the Role This is an exciting position where applicants are invited to join a multi-disciplinary team of bioengineers, biomedical scientists, and computer scientists working together at Queen