Job Description
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.
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: 1) explore cancer-specific genomic, epigenetic, and metabolic alterations, molecular systems pharmacology, and network biology and 2) 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, identifying biomarkers and pinpointing the molecular determinants of response to cancer therapy.
Qualifications and Job Details
Required and Preferred Skills
- Ph.D. in a relevant field, including: Statistics, Mathematics, Data Science, Physics, Engineering, or Computer Science, or a degree related to Biology with substantial experience in computational and statistical work. Individuals in the final stages of Ph.D. submission will be considered as well as Ph.D. graduates within 5 years of graduation.
- Strong knowledge and experience in coding (R/Python or similar languages; the lab has a significant, existing codebase in R)
- Technical expertise in machine learning and/or mathematical modeling
- Prior and demonstrated experience working with -omics data (e.g., RNAseq, copy number, mutation, methylation, proteomics)
- 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 and high-performance computing
- Experience with machine learning frameworks (Pytorch/Tensorflow or similar)
- Experience with mass spectrometry-based proteomics data analysis is highly desirable
- Experience with using network-based analyses (graph theory) and software/resources (graph and/or pathway databases) is highly desirable
- Experience with single-cell data analysis is highly desirable
- Experience working in collaborative interdisciplinary environments
About the NCI Center for Cancer Research
The Center for Cancer Research (CCR) is home to nearly 250 basic and clinical research groups located on two campuses just outside of Washington, D.C. CCR is part of the National Cancer Institute (NCI) and makes up the largest component of the research effort at the National Institutes of Health (NIH). Centrally supported by long-term funding and a culture of complete intellectual freedom, CCR scientists are able to pursue the most important and challenging problems in cancer research. We collaborate with academic and commercial partners and advocacy groups across the world in efforts to prevent, diagnose and treat cancer and HIV/AIDS. The CCR research portfolio covers the full spectrum of biological and biomedical research. Our work ranges from basic to translational and clinical, and our clinical trials are conducted in the NIH Clinical Center, the world’s largest hospital dedicated to clinical research that offers a robust infrastructure to support CCR’s patients on an estimated 250 open studies. The success of CCR is grounded in an exceptionally strong discovery research program that provides the foundation for the seamless translation of insights from bench to bedside. Read more about CCR, the benefits of working at CCR and hear from our staff on their CCR experiences.
Bethesda
Bethesda is one of the most highly educated communities in the United States and has a nationally renowned school system. The city is a thriving suburban center close to Washington, D.C., and home to many restaurants, retailers and a flourishing arts and entertainment district.
Contact Links
- https://ccr.cancer.gov/staff-directory/augustin-luna
- https://www.nlm.nih.gov/research/researchstaff/LunaAugustin.html
- Google Scholar: https://scholar.google.com/citations?user=u2dgLp8AAAAJ&sortby=pubdate
- Summary of NIH as a Training Environment (Reputation, Cost of Living, Social Climate): https://github.com/cannin/nih
Related Recent Articles
- Causal Interactions: Molecular Data Meets Pathways: https://pubmed.ncbi.nlm.nih.gov/34179843/
- Understanding Drug Resistance through Network Data: https://pubmed.ncbi.nlm.nih.gov/36103824/
- CellMiner Cross-Database for Pharmacogenomics: https://pubmed.ncbi.nlm.nih.gov/33196823/
- scPerturb: Harmonized Single-Cell Perturbation Data: https://www.biorxiv.org/content/10.1101/2022.08.20.504663v3