Computational Biology Scientist – Center for Protein Degradation
Dana Farber Cancer Institute
The Center for Protein Degradation (CPD) seeks a highly motivated individual to join the team as a computational biologist to develop sophisticated computational approaches to identify therapeutic targets uniquely suitable for degradation. The candidate will develop strong working relationships with biologists, biochemists, chemical biologists and chemists to nominate targets, provide strong data driven rationale, and analyze integrated omics data sets.
The ideal candidate has an extensive working experience in integrated analysis of large-scale omics and pharmacological profiling data sets. The candidate will create new algorithms for analyzing relevant data in public domains and proprietary proteomics to provide novel biological insights into the relationship between target degradation and related human diseases.
Dana-Farber Cancer Institute (DFCI) and Deerfield Management have entered a multi-year collaboration to create the Center for Protein Degradation (CPD) at DFCI led by Drs. Fischer and Gray. The goals of the Center for Protein Degradation are to create a next-generation protein degrader platform and interrogate and advance a large portfolio of protein degrader targets. This is an exceptional opportunity to join a newly founded research center that is pushing the boundaries of targeted protein degradation research and accelerating the translation of basic science into clinical solutions. This individual will be an important member of our research team and will be centrally involved in assisting various research projects primarily involving protein biochemistry. In addition to the bench-based research, responsibilities will also include some aspects of laboratory management and organization. Training is available in all aspects of experimental research.
Significant progress has recently been made towards chemically induced targeted protein degradation using heterobifunctional small molecule ligands (often referred to as degraders or PROTACs). Small molecule degraders open up a new opportunity for modulating proteins that are difficult to target previously such as transcription factors. It provides new pharmacological tools to investigate new biology and therapeutic modality to treat difficult diseases.
About Dana Farber:
Located in Boston and the surrounding communities, Dana-Farber Cancer Institute brings together world renowned clinicians, innovative researchers and dedicated professionals, allies in the common mission of conquering cancer, HIV/AIDS and related diseases. Combining extremely talented people with the best technologies in a genuinely positive environment, we provide compassionate and comprehensive care to patients of all ages; we conduct research that advances treatment; we educate tomorrow's physician/researchers; we reach out to underserved members of our community; and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.
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.
• PhD in computational biology, applied mathematics, statistics, or related fields with at least 2 years of postdoctoral experience
• Extensive working knowledge in analyzing large scale omics data sets in public domains
• A strong background in human disease biology and statistics
• Programming/scripting skills are essential for this position.
• Must demonstrate outstanding personal initiative and the ability to work effectively as part of an interdisciplinary team.
• Excellent communication and presentation skills.
• Scientific drive; demonstrated by a proven track record of publications in peer reviewed journals
• Demonstrated ability to work in a fast-paced and dynamic environment.
• Excellent organizational and prioritization skills. Strong attention to detail
• Ability to collect and analyze experimental data, prepare research publications and communicate results.
• Experience with machine learning, cheminformatics, and proteomics is desired
To apply, please visit: social.icims.com/viewjob/pe15728877938644bf6c