Sort by
Refine Your Search
-
quality, and health. We seek a PhD or Postdoc to work on either of the two topics: Autonomous reaction discovery: combining quantum chemistry, machine learning, and automation to chart oxidation pathways
-
- Epigenomics, Machine Learning & 3D Genome Biology Employer NYU Langone Health, Skok Lab Location New York City, New York (US) Salary Postdoc: $70,000+ annually, plus benefits; Senior Computational Biologist
-
scalable machine learning and AI tools that integrate spatial multi-omics data with mechanistic models across molecular, cellular, and tissue scales. The postdoc will also have the opportunity to make major
-
[Journal Cover]), artificial intelligence (PMID:35411337 [ Nature Machine Intelligence 2022]), genomics and multi-omics ( Nature Neuroscience 2026 [in press]; PMIDs:33558758 [ Nature Genetics 2021
-
/software co-design and operating/runtime systems. Typical application domains are e.g. signal-/image processing and machine learning. Tasks: modeling and simulation of near-memory computing
-
Postdoc Position for Computational Genomics, AI Precision Oncology, Cancer Biology and Immunobiology
University of Pittsburgh, Pittsburgh , Pennsylvania, US | Pittsburgh, Pennsylvania | United States | 2 days agoprecision oncology: Build mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable
-
learning techniques in multiple modalities of medical imaging (e.g. fundoscopy images, OCT scans, MRI, CT, X-ray and digital pathology). We bridge the gap between machine learning research and clinical
-
CIC bioGUNE (Asociación Centro de Investigación Cooperativa en Biociencias) | Bilbao, Pais Vasco | Spain | 17 days ago
goal, the candidate will combine a gene network-based approach with a machine learning model (foundational model) to propose protocols for the sequential induction of transcription factors to
-
, including competitive water adsorption (humidity) effects establishing AI-supported algorithms for material selection in close feedback loops with experimentalists machine learning for process implementation