AI/ML Computational Biologist - Postdoctoral Researcher

Position Postdoctoral Research Staff Member Organization and Term Integrative Multi-Omics Group. 2‑year term appointment with potential extension to 3 years. Responsibilities Develop and apply machine learning methods for prediction and representation learning from high‑dimensional biological data. Contribute to the design and implementation of workflows for integrative analysis of bulk, single‑cell, spatial, and multimodal datasets. Investigate, develop, and apply approaches for multimodal data fusion, cross‑dataset integration, and transfer learning. Train, adapt and evaluate self‑supervised and foundation models for omics data. Develop and apply interpretable models linking molecular states to disease trajectories and host‑response phenotypes. Process and analyze large‑scale sequencing and other omics datasets. Present research findings at seminars, conferences, and technical meetings. Contribute to research design and project execution. Collaborate in a multidisciplinary team environment. Publish results in peer‑reviewed journals. Perform other duties as assigned. Required Qualifications PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, Data Science, or a related field. Strong background in machine learning, statistical modeling, computational biology, or a related quantitative discipline. Experience analyzing high‑dimensional biological data such as genomics, transcriptomics, or related modalities. Proficiency in Python and R. Experience with ML frameworks such as PyTorch, TensorFlow, or similar. Familiarity with Linux/Unix and scientific computing workflows. Demonstrated ability to conduct high‑quality research and publish results in peer‑reviewed journals. Demonstrated ability to work effectively in a collaborative research environment. Strong written and verbal communication skills. Desired Qualifications Experience with deep learning or probabilistic modeling approaches, such as variational autoencoders, scVI, or related methods. Experience with single‑cell, spatial, and/or multimodal omics data. Experience with multiomic data integration, including multimodal single‑cell datasets. Experience with transfer learning, domain adaptation, cross‑dataset integration, or batch correction. Experience with transformers, self‑supervised learning, or pretrained models for biological data. Experience training and scaling machine learning models on large datasets. Interest in immunology, host‑pathogen biology, or disease modeling. Pay $123,048 Annually Benefits Flexible Benefits Package (401(k)) Relocation Assistance Education Reimbursement Program Flexible schedules (depending on project needs) Security Clearance None required. However, assignments exceeding 179 cumulative days per calendar year require the Personal Identity Verification process and a background investigation. Equal Employment Opportunity We are an equal‑opportunity employer committed to providing a workplace free of discrimination. All qualified applicants are considered for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or other characteristics protected by law. Reasonable Accommodation We strive to create an accessible and inclusive process for all candidates. If you need accommodation during the application or interview process, please use the online form to submit a request. #J-18808-Ljbffr