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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 hours ago
related field and have a strong background in fMRI data analytic techniques. Computational and quantitative skills are highly desirable. While there will be opportunities for data collection and assessment
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their expertise in being part of a laboratory delivering assay results to underpin a multicentre drug screening programme in ALS. This post is suitable for a bioscience graduate with excellent organisational skills
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Musculoskeletal Sciences (NDORMS) is part of the Medical Sciences Division and is the largest European academic department in its field, running a globally competitive programme of research and teaching. The
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 5 hours ago
or related areas; demonstrated publications; strong computational skills (e.g., Python, MATLAB); and experience analyzing large datasets and communicating results effectively. PREFERRED : Experience with
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may include work at Jefferson Lab, the Electron-Ion Collider (EIC) program, detector research and development, and applications of AI in nuclear physics. Applications received by Tuesday, November 4
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of CH previously developed in our group. About You We are seeking quantitatively-minded researchers with a PhD in physics, mathematics, computer science, mathematical/computational biology, evolutionary
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MRI (fMRI), functional Ultrasound Imaging (fUSi) and computational modelling of emotion-related behaviours. This is an exceptional opportunity to develop your research portfolio within a team of
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Position Summary Working on research program centered on unraveling the intricate molecular mechanisms that govern DNA repair and replication, with a particular focus on nick sealing processes by human DNA
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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research. The ideal fellow will be interested in developing and applying novel computational algorithms to novel datasets generated in the setting of non-neoplastic and neoplastic disease. Key