105 engineering-computation-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" research jobs at Stanford University
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, genetics, and neurodevelopment, along with access to state-of-the-art imaging technology and advanced computational resources. The fellow will have structured opportunities for professional development
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based on performance and funding). Appointment Start Date: Flexible Group or Departmental Website: https://med.stanford.edu/neurology.html (link is external) How to Submit Application Materials: Please
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Appointment Term: July/August 1, 2026 to June/July 31, 2027 (renewable) Appointment Start Date: August 1, 2026, with some flexibility Group or Departmental Website: https://scale.stanford.edu/ (link is external
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Postdoc Appointment Term: 2026-2028 Appointment Start Date: Early 2026 Group or Departmental Website: https://med.stanford.edu/bronte-stewart-lab.html (link is external) How to Submit Application Materials
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Date: As soon as possible Group or Departmental Website: https://naturalcapitalproject.stanford.edu/ (link is external) How to Submit Application Materials: Send an email with your attachments
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, candidates should possess a strong background in quantitative fields such as Mathematics, Physics, Engineering, or Computer Science. This is a collaborative, cross-functional team, and project assignments will
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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
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interest in translational science. The postdoctoral fellow will work closely with Dr. Vivek Charu and Dr. Brooke Howitt. Required Qualifications: PhD in Biostatistics, Bioinformatics, Computational Biology
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. Prevalent TCR clones will undergo reverse engineering to deduce the peptide bound, and this information used to generate MHC tetramers to study the induction of these clones during the anti-tumor response
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testing of the Identity Project and the E4 Teacher Professional Development program in the United States – identifying feasible and effective strategies to support educators as they prepare to implement