We are always looking for individuals who are enthusiastic, innovative thinkers, and who enjoy team-oriented research, to join our group.
New job posting (posted on 3/20/20): Post-doctoral fellow, Computational Data Science, ICBI, Georgetown University
The Georgetown University Innovation Center for Biomedical Informatics (ICBI) is a multi-disciplinary, academic hub for innovative research in the field of data science. Established in Spring 2012, our vision is to enable a more individualized approach to healthcare. Our mission is to enhance clinical and translational research at Georgetown, through collaborative research partnerships involving biomedical data analysis. This includes educating the next generation of biomedical scientists and physicians, for whom informatics is becoming a routine part of research and healthcare delivery.
We seek a computational scientist to join our vibrant multi-disciplinary team in Dr. Madhavan’s lab to continue to expand our computational expertise in the area of precision medicine. This is an exciting opportunity to become part of and grow into a faculty position within a world-renowned medical center with expertise in biomedical informatics, health data science, clinical oncology, molecular diagnostics and real world data analytics.
You will work closely with team members with diverse expertise to implement cutting edge computational methods and software for personalized medicine advances to support our projects in the ClinGen, Cancer center, CTSA, collaborations with National labs and other NIH-funded research. You should be someone who is comfortable with rapid, agile computational development in a high intensity and rapidly evolving research and development environment. You must be creative, self-driven and work independently, yet be an excellent communicator and coordinate specific projects within a matrix organization; fundamentally, you must be passionate about the potential to utilize big data to improve health outcomes. You must be adept at coming up with new ideas and solutions and to adapt to new technologies and changing priorities
Key responsibilities include, but are not limited to:
- Develop and implement novel algorithms for matching patients with drugs based on multi-omic (genomic, proteomic, and methylation) and clinicopathologic data from Electronic Health Records (EHRs), Social Determinants of Health (SDOH) and other sources
- Work closely with the technology team to architect, develop, maintain, and document computational infrastructure for large-scale omics data management and analysis using high-performance cloud computing resources (e.g. Google Cloud Computing or Amazon web services)
- Adopt and/or develop natural language processing tools and workflows for extracting relevant details from scientific literature and other unstructured sources of information
- Integrate data from external datasets (e.g. TCGA, SEER) with in-house pipelines
- Apply data visualization techniques to effectively present data
- Propose, prototype and implement web based technologies for organizing, modeling, and analyzing biomedical data that can help connect genes to drugs and diseases
- Develop novel bioinformatics and computational methods and techniques to model large volumes of disparate data towards the identification of new patterns and hypothesis
- Present the work and results at conferences and workshops, independently develop and write manuscripts for peer-reviewed journals and assist in the writing of grant proposals
The ideal candidate will have broad expertise in biomedical informatics and/or computational biology with a strong knowledge of systems biology and fluent in computational approaches.
Additional requirements include:
- Expertise in machine learning, deep learning and other AI methods in health and life sciences datasets
- Proficient in causal inference modeling and other advanced statistical approaches in econometrics, outcomes, or health services research
- Be comfortable with rapid end-to-end prototyping for data science applications
- Expertise in advanced computational biology methods such as systems biology and network analysis, graph databases and data mining tools
- Knowledge of open/public/private databases including but not limited to clinically relevant human variants, clinical trials and pharmacogenomics and drug databases
A PhD in Computational Biology, Computer Science, Bioinformatics, Biomedical Informatics, Biostatistics or related analytical field is essential. Excellent verbal and written communication and presentation skills in English are necessary.
Please send your resume and a brief cover letter to email@example.com. Georgetown ICBI is a great place to begin and expand your informatics career. Georgetown University values diversity and is an equal opportunity employer and routinely processes visa applications as needed for students, fellows and trainees. Women and minority candidates are strongly encouraged to apply.