Cancer Computational Biologist (Luna Lab, NLM/NCI) (Postdoctoral Fellow)

Organization National Library of Medicine and National Cancer Institute, Bethesda, MD and surrounding area The Luna lab is jointly affiliated with the National Library of Medicine (NLM) and the National Cancer Institute (NCI). The dual ambitions of the lab are to make biomedical data and information accessible, as well as, to advance cancer research that helps people live longer, healthier lives. We seek outstanding, highly motivated, and skilled candidates to join our team with the goal of advancing novel cancer therapeutic strategies. About the position This position offers a unique opportunity to contribute collaboratively to cutting-edge research in the field of cancer therapeutics and precision medicine that spans both basic and translational science objectives. The successful candidates will develop novel bioinformatic machine learning methodologies to: Explore cancer-specific genomic, epigenetic, and metabolic alterations, molecular systems pharmacology, and network biology. and Understand molecular mechanisms of drug response and drug resistance to achieve precision medicine. These strategies will aim to understand the fundamental rules for how cells respond to external perturbation. In addition, selected applicants will have the opportunity to contribute to the translational clinical program of the NCI, aiming to support clinical decision-making by exploring cancer heterogeneity using both pre-clinical models (e.g., cell lines, patient-derived xenografts, organoids) and patient datasets, as well as, identifying biomarkers and molecular determinants of response to cancer therapy. We are offering full‑time postdoctoral fellow positions, available immediately and renewable on a yearly basis. Initial appointments will be for 1 year, with possible extensions up to 5 years. The NIH offers a competitive stipend, a stipend supplement for comprehensive health insurance, and is dedicated to the continued education and career development of all its research staff. These positions are subject to background checks. The National Library of Medicine (NLM) pioneers new ways to make biomedical data and information more accessible; and builds tools for better data management and personal health. NLM’s cutting‑edge research and training programs (with a focus on artificial intelligence (AI), machine learning, computational biology, and biomedical informatics and health data standards) help catalyze basic biomedical science, data‑driven discovery, and health care delivery. If we are interested, you will be contacted by Dr. Luna. PhD in a field relevant to biomedicine, including: Bioinformatics, Biomedical Engineering, Mathematics, Data Science, Physics, or Computer Science, or a degree related to Biology with substantial experience in computational and statistical work. Individuals in the final stages of PhD submission will be considered as well as PhD graduates within 5 years of graduation Prior and demonstrated experience in cancer research Strong knowledge and experience in coding (R/Python or similar languages) Prior and demonstrated experience analyzing -omics data (e.g., RNAseq, copy number, mutation, methylation, proteomics) Technical expertise in machine learning and/or mathematical modeling An interest in applying computational methods to biological problems A demonstrated ability to generate and pursue independent research ideas Excellent communication skills, written and verbal as evidenced by publications, preprints, and/or conference presentations Dedication to reproducible research and open science Foundational knowledge in Bioinformatics, Systems Biology, and/or similar fields Foundational knowledge in Mathematics, Statistics, and/or Data Science Familiarity with software development practices Experience with machine learning frameworks (Pytorch or similar) Experience with using network-based analyses (graph theory) and software/resources (graph and/or pathway databases) is desirable Experience with single-cell data analysis is desirable Experience working in collaborative interdisciplinary environments Disclaimer/Fine Print U.S. citizens and permanent residents are eligible to apply. NIH welcomes foreign nationals with the exception of individuals from this list . #J-18808-Ljbffr Office of Intramural Training & Education