We have an opening for a highly motivated Postdoctoral Researcher to conduct research in computational structural biology to develop methods for predicting protein-protein interactions in host-pathogen systems using deep learning (DL). Current structure prediction tools such as RoseTTAFold3, AlphaFold3, and ESMFold2 excel at monomeric structure prediction and predicting known protein complexes. However, these tools struggle to identify which proteins interact and which do not. You will work to develop specific models that can discriminate between interacting and non-interacting proteins. You will be an integral member of an interdisciplinary, cross-institution team working with computational biologists, and experimental biologists. You will leverage computational tools and work to develop new DL-based approaches and tools to predict binary interactions, specificity, and structure. You will also work closely with an existing team of computational biologists to understand current capabilities and jointly develop a vision for development of next generation protein design models and tools. You will present your work regularly and publish your research and findings, which includes occasional travel. This position is in the Computational Engineering Division (CED), within the Engineering Directorate. Interested candidates should submit a complete application that includes:  Cover letter (1-2pgs) describing the following:  Research interests A description of graduate work and greatest scientific accomplishments How previous work (postgraduate/graduate/prior research experience) makes you a strong candidate for developing ML methods for predicting protein-protein interactions. What are your career goals (briefly) How do you seek to approach this research area? (~1 paragraph)  Curriculum vitae including full publication list Contact information for three professional references  A complete application includes a cover letter, CV, and references. Incomplete applications will not be considered. Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week. In this position, you will Conduct research, and contribute to designing, analyzing, and extending DL-based tools for prediction and optimization of protein interaction specificity. Participate in the development of protein sequence and structure computational frameworks and analysis tools. Collaborate with external partners (Universities, Industry, other National Laboratories) to advance computational biology simulation efforts. Prepare complex and detailed progress reports, written analyses, and verbal briefings to support project needs and deadlines and to present research results to sponsors. Independently pursue the development of new and innovative research methods relevant to the needs of Laboratory programs and/or external funding agencies. Contribute to proposals and statements of work. Publish research results in peer-reviewed scientific or technical journals and present results at external conferences, seminars, and/or technical meetings. Travel as needed to coordinate with research collaborators and to attend external meetings and conferences. Perform other duties as assigned.