Fellow, Oncology Health Economics and Outcomes Research (HEOR)
Precision Health AI (PH.AI) is developing the leading artificial intelligence (AI) platform for oncology built on deep clinical oncology data to enable the practice of precision medicine for better cancer patient care and to accelerate cancer-related drug development, trials, and real world evidence for the benefit of patients, oncologists, and the cancer care ecosystem. To learn more, visit www.precisionhealth.ai
As a healthcare technology company, PH.AI’s AI platform is trained specifically for oncology, leverages proprietary and unique data sources, and integrates seamlessly into the existing workflows of healthcare manufacturers, providers, and payers, with the goal of improving oncology outcomes. With the aid of its industry-leading AI platform, PH.AI analyzes large sets of cancer patient data from a variety of settings including observational studies, clinical trials, and real world evidence such as genomic sequencing data, EMR/EHR, and claims, to identify which treatments work for which cancer patients, why, in what context, and at what cost, with the goal of developing tailored treatment regimens for each patient. PHAI is unlocking the promise of precision medicine, one cancer patient at a time.
The Fellows program at Precision Health AI (PH.AI) offers exceptional scientific and medical trainees the opportunity to gain industry experience by conducting and publishing ground-breaking research at the intersection of oncology, population outcomes research, data science, and technology.
Fellows will utilize the consolidated PH.AI oncology data resources including electronic medical/health records (EMR/EHR), claims, patient-level genetic/molecular data, patient reported outcomes data, and other data sets in HEOR projects. Work is performed under the general direction of the Head of Strategy & Operations, with day to day oversight from the Director of Oncology Health Economics and Outcomes Research (HEOR).
- Research Publication: The core deliverable at the end of the Fellowship is at least 1 submitted manuscript for publication in a top scientific/medical journal. Under the supervision of the Head of Strategy & Operations, and with support from the Director of Oncology HEOR, each Fellow will be assigned to a core publication topic, and will own the entire research process from discovering the research question, setting research objectives and hypotheses, developing and executing statistical analyses plans, extracting insights and drawing conclusions
- Journal Club: Fellows are expected to present relevant, and high impact scientific/medical articles in the area of oncology, data science, and/or artificial intelligence during the weekly PH.AI journal clubs
- Custom Analytics for Client HEOR projects: Fellows may be assigned to conduct portions of research analysis, which are part of PH.AI client projects
- Academic/Provider Partnership Efforts: Fellows will play an important role in championing the PH.AI data, technology, and capabilities to academic institutions and other potential life science partners
- Thought Leadership: Fellows will monitor, and evaluate trends in oncology, and will develop expertise in all areas of oncology drug development including preclinical research, clinical trials, sales/commercialization, market access, HEOR, etc.
- Ad Hoc Research Projects: Fellows will support the Scientific and Medical Affairs team on ad hoc projects as needed
- Current MS, MD, PhD, and MD/PhD students, Post-doctoral Fellows, Medical Residents, Medical Fellows, and other scientific/medical trainees
- Minimum of 6-month commitment (1 – 2years is ideal)
- Availability to work minimum of 10 hours/week
- Track record of scientific achievement and publication
- Located in Boston, MA or New York, NY
- Data and analytics nerd – you love data, love analyzing it, and even better, you love discovering novel insights from data
- Strong presentation and communication skills – superior writing ability is required
- Ultimate team player with a “team above self” attitude
- Quick learner that can develop expertise in new areas and data analysis tools quickly
- Self-starter that appreciates guidance, but does not need it to “get going”
- Problem solver that sees what’s possible not what’s impossible
- Tenacious in overcoming data challenges