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astroparticle physics, particle physics, and mathematical physics. The cosmology and astroparticle team (https://astrocosmolapth.com ) conducts research on large-scale cosmic structure, microwave and infrared
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existing structural and functional MRI data, acquire new data in collaboration with clinical researchers, and prepare publications and conference presentations. - Study preparation - Data acquisition (MRI
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). The Eisenmesser laboratory is located in a highly collaborative structural biology environment with access to: Bruker 600 MHz and 900 MHz NMR spectrometers with cryoprobes An on-site 200 kV Talos Arctica cryo-EM
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and/or diplomas, if applicable. Enrolment in Master's degree in Computer Science or Informatics Engineering. Work plan: The objective is to develop a prototype system that processes structured
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members and center initiatives. The dual structure of reporting and funding is designed to integrate applied research with strong industry engagement and strategic alignment of MDFRC. Key Responsibilities
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from the School of Physical and Mathematical Sciences with the School of Chemical and Biomedical Engineering. It is jointly run by the College of Science and the College of Engineering (https
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to support the position. We also take into consideration market benchmarks, if and when appropriate, and internal equity to ensure fair compensation relative to the university’s broader compensation structure
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 15 hours ago
Experience, Skills, Training/Education: Experience with pangenomics, structural variation, and synteny analysis. Background in ecological genomics or plant adaptation. Experience mentoring students
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
insights through iterative, hypothesis-driven computational analysis. 2) Characterizing the landscape of structural mutations—including intragenic rearrangements (IGRs)—across cancer types and modeling
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language models to whole genome sequencing data - Develop algorithms and neural network architectures for the prediction of structured outputs (i.e. trees, graphs) - Implement and develop methods