Data Science Innovation Postdoctoral Fellow: Cancer Combination Therapy

Job Description Summary

We are thrilled to open applications for our Data Science Innovation Fellowship. This applied 3-year research program is set to change the way we approach drug discovery, offering fellows a unique chance to train in data science and AI (DS&AI) for biomedical research. As a talented fellow, you will learn to apply your computational skills to make a difference for patients and reimagine medicine at Novartis.We are thrilled to open applications for our Data Science Innovation Fellowship. This applied 3-year research program is set to change the way we approach drug discovery, offering fellows a unique chance to train in data science and AI (DS&AI) for biomedical research. As a talented fellow, you will learn to apply your computational skills to make a difference for patients and reimagine medicine at Novartis.

 

Job Description

Internal Job Title: Innovation Postdoctoral Fellow

Location: Cambridge, onsite

About the role:

We are thrilled to open applications for our Data Science Innovation Fellowship. This applied 3-year research program is set to change the way we approach drug discovery, offering fellows a unique chance to train in data science and AI (DS&AI) for biomedical research. As a talented fellow, you will learn to apply your computational skills to make a difference for patients and reimagine medicine at Novartis.

Drug hunting is a team sport, and you will gain experience in DS&AI for drug discovery as part of a multi-disciplinary team in Biomedical Research. You will drive innovation by deploying cutting-edge data approaches in collaboration with a vibrant and diverse community of over 300 data scientists globally. The program provides a unique platform to work on real-world, biomedical data at scale, rarely accessible in academia. Under the guidance of experienced mentors, you’ll embark on a journey of professional growth, benefiting from a tailored training program with built-in time for a mini-sabbatical in other areas of Novartis and for attending conferences/workshops.  

Biomedical Research is the home of a vibrant postdoctoral community connected through science and events supporting the professional growth of our fellows, including monthly seminars and an annual Research Day Symposium. Seize this chance to be at the forefront of DS&AI and shape the future of drug discovery!

Resistance to cancer therapies often arises because not all cancer cells in the tumor are sensitive to the treatment, and hence combination treatments may be needed to effectively eliminate multiple subpopulations of cancer cells. This is bolstered by the emerging notion that most clinically successful cancer drug combinations demonstrate independence, with the combination being simply additive rather than synergistic (Hwangbo et al. Nature Cancer 2023). This fellowship project aims to leverage patient tumor single-cell data to design additive combination therapies with non-overlapping resistance mechanisms. This will provide preclinical strategies to increase the likelihood of clinical trial success. 

Start date: Winter 2024

Key responsibilities

As a Data Science Innovation Fellow, you will:

• Work in a collaborative ecosystem with data scientists, wet lab biologists, and other postdoctoral fellows to pursue cutting edge strategies for developing more effective cancer therapy
• Push the limits of biological and computational knowledge in tandem to achieve innovative results
• Develop skills and awareness of real-world drug discovery and development in a supportive and collaborative training environment
• Identify existing computational methods, or develop new methods as needed, for predicting the drug response of individual cancer cells
• Develop biological rationale for why given drug combinations may or may not be additive versus synergistic or antagonistic
• Leverage patient tumor data to predict which patient populations would be most likely to respond to a given combination therapy

Role requirements:

• PhD in in computational biology, bioinformatics, systems biology, biological engineering, data science, statistics, computer science, biology, chemistry, physics, or a related field (PhD students in the last year of their thesis work are eligible to apply)
• Familiarity with fundamental concepts in bioinformatics, statistics, and cell biology
• Experience analyzing high-dimensional data sets, preferably ‘omics data sets (e.g., single-cell RNA-seq, bulk RNA-seq, epigenetics, proteomics)
• Knowledge of cancer biology, genomics, and/or immuno-oncology preferred
• Fluency in one or more programming languages (e.g., Python, R, MATLAB)
• Strong pu