Skip to main content
Tallo logoTallo logo

Find Jobs

Find Jobs Near You – Available Work in Your Location

Skip to job details

Back to Results

Apply for this opportunity

To apply for this job, you'll continue to an external website or email application.

National Institutes of Health

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

Review key factors to help you decide if the role fits your goals.
Pay Growth
?
out of 5
Not enough data
Not enough info to score pay or growth
Job Security
?
out of 5
Not enough data
Calculating job security score...
Total Score
70
out of 100
Average of individual scores

Were these scores useful?

Job Description

Cancer Computational Biologist (Luna Lab, NLM/NCI) (Postdoctoral Fellow) National Institutes of Health - 4.3 Bethesda, MD Job Details Full-time 12 hours ago Benefits Health insurance Qualifications Computational research Academic research projects Software coding Doctor of Philosophy Oncology research Clinical data analysis Bioinformatics data analysis Data analysis software Full 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. 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.
Related Articles Causal Interactions:
Molecular Data Meets Pathways Understanding Drug Resistance through Network Data CellMiner Cross-Database for Pharmacogenomics sc
Perturb:
Harmonized Single-Cell Perturbation Data Additional Links Augustin Luna - CCR staff profile , NLM profile , Google Scholar Summary of NIH as a Training Environment (Salary, Reputation, Cost of Living, Social Climate) About the NLM 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. About the
NCI/CCR/DTB
The National Cancer Institute Center for Cancer Research (NCI-CCR) is the largest division of the NCI; it encompasses various branches such as the NCI Developmental Therapeutics Branch. The NCI CCR has a mandate to confront the special challenges presented by rare cancers as well as cancers that may be predominant in medically underserved populations. One way in which the NCI CCR addresses this mandate is by conducting clinical trials that recruit patients with rare cancers thereby generating unique data to advance research in these cancers. While rare cancers affect low numbers of patients, as a group, they account for about a quarter of all cancers, as well as a quarter of all cancer deaths each year . What you'll need to apply To , please send the following: Cover letter (1 page max) describing your: 1) research experiences, 2) training goals, and 3) preferred starting date. Mention projects or articles of the Luna group of interest and explain your potential role. Updated CV including bibliography It is suggested that links to a code repository URL(s) be included in your application with code attributable to the applicant Contact information (name, institute, email, phone) for 3 references to Augustin Luna, Ph.D., via email. Write "Postdoctoral Application" in the subject heading. If we are interested, you will be contacted by Dr. Luna. Contact name Augustin Luna Contact email Qualifications Essential qualifications 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 Desirable qualifications 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

Benefits

  • Bonuses/Stipends
  • Health Insurance
  • Dental Insurance