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Field
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position that holds responsibilities primarily contributing to the research mission of the department through scholarly impact and an externally funded research program in the areas of wireless and network
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of Engineering Position Headcount 2 Position Title Student Research Assistant- Social Network Analysis (MR-QAP) Academic Year Spring 2026 Term or Semester Spring Is this Role for an Undergrad or Grad Student
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About the Opportunity SUMMARY The lab of Professor Albert-László Barabási is looking for Postdoctoral Research Associates in the area of network science, nutrition, biological networks, machine
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Details Title Postdoctoral Fellowships in Networking Support for Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer Science Position
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in the field of network science, with applications to nutrition, biological networks, network medicine, and the science of science. The position involves developing and applying computational
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computational skills and expertise in causal inference or network science are desired but not required. Start date and term are negotiable. Additional Qualifications Special Instructions For more information
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to uncover novel regulators and mechanisms of neuromodulation. Develop computational approaches to model spatiotemporally resolved signaling networks. Academic environment: Stanford University provides a
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gene regulatory network to influence phenotype”. Applications will be received until the position is filled. Basic Qualifications We seek a computational genomics postdoc to develop new methods and tools
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of Science, Mathematics, Computer Science, or a closely related field. Demonstrated computational expertise (e.g., Python, network analysis, data wrangling). A research profile that engages with questions
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
immunotherapies, integrating graph neural networks, regulon-aware pooling, and transfer learning with biological regulatory networks. 4) Developing and validating computational biomarkers (IGR burden, TAA burden