We are seeking a Postdoctoral Research Staff Member to conduct research at the intersection of artificial intelligence (AI), machine learning (ML), and computational biology. The successful candidate will apply and adapt state-of-the-art AI/ML approaches to understand host-response dynamics in complex biological systems. Research will focus on integrating large-scale multiomic datasets, including bulk, single-cell, spatial, and multimodal data, from animal models and human cohorts to identify molecular programs associated with disease progression, immune responses, and biological resilience. The candidate will leverage modern machine learning approaches, including deep learning, self-supervised learning, and biological foundation models, to generate biologically meaningful insights from diverse datasets and develop predictive models that generalize across biological systems. This position is in the Integrative Multi-Omics Group and offers the opportunity to work under the guidance of senior scientists on high-dimensional biological data at scale in a collaborative, multidisciplinary environment. This is a two-year term appointment with the possibility of extension to a maximum of three years. In this role you will 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 multiomic datasets (bulk, single-cell, spatial, and multimodal). 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.