Postdoctoral Research Fellow - Program in Regulatory Science - Trippa Lab

Job Details

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Job ID:
32893

Location:
450 Brookline Ave, Boston, MA 02215

Category:
Fellowships

Employment Type:
Full time

Work Location:
PTL Remote: 2-3 days remote/wk

Overview

Open position for a postdoctoral fellow in Biostatistics at Harvard.  

This position will be based at Dana-Farber Cancer Institute and supervised by Lorenzo Trippa (https://www.hsph.harvard.edu/lorenzo-trippa/) The development and translation of effective precision medicines requires generation of information regarding both efficacious therapeutics and putative biomarkers that predict that efficacy. The exponential increase in potential biomarker information that is available for any given patient or disease, including genomic biomarkers, has created challenges with respect to the best methods to support both the scientific development and the regulatory decision-making required to bring new medicines to clinic. The Program in Regulatory Science develops new approaches and quantitative methods to support the discovery of new treatments in precision medicine and collaborates with groups at Dana-Farber in the development of innovative clinical trials.

Our work focuses on major areas of clinical trial design, including:

  • Design and implementation of biomarker-based platform trials in oncology.
  • Novel statistical methods for the analyses of clinical trials that leverage real-word data
  • Development of novel algorithmic or model-based approaches to phase I and II studies.
  • Biomarker-driven subgroup analyses in clinical trials.

The mission of the Program in Regulatory Science (PRS) (https://www.dana-farber.org/research/departments-centers-and-labs/departments-and-centers/program-in-regulatory-science/) is to generate novel approaches for the development of therapeutics and biomarkers through preclinical and clinical trial designs, pipeline modeling, and scientific contributions in regulatory science.

Located in Boston and the surrounding communities, Dana-Farber Cancer Institute is a leader in life changing breakthroughs in cancer research and patient care. We are united in our mission of conquering cancer, HIV/AIDS and related diseases. We strive to create an inclusive, diverse, and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.

Responsibilities

Your work focuses on major areas of clinical trial design, including:

  • Design and implementation of biomarker-based platform trials in oncology.
  • Novel statistical methods for the analyses of clinical trials that leverage real-word data
  • Development of novel algorithmic or model-based approaches to phase I and II studies.
  • Biomarker-driven subgroup analyses in clinical trials.

Qualifications

Candidates must have received a PhD in Statistics, Biostatistics, Computer Science, or related field. Please include CV in application. 

At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and inclusive environment where every patient, family, and staff member feels they belong.  As relentless as we are in our mission to reduce the burden of cancer for all, we are equally committed to diversifying our faculty and staff.  Cancer knows no boundaries and when it comes to hiring the most dedicated and diverse professionals, neither do we. If working in this kind of organization inspires you, we encourage you to apply.

Dana-Farber Cancer Institute is an equal opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other groups as protected by law.

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