Memorial Sloan Kettering Cancer Center (MSK) is one of the world’s premier cancer centers, committed to exceptional patient care, leading-edge research, and superb educational programs. The blending of research with patient care is at the heart of everything we do. The institution is a comprehensive cancer center whose purposes are the treatment and control of cancer, the advancement of biomedical knowledge through laboratory and clinical research, and the training of scientists, physicians and other health care workers.
The Schultz lab is seeking a highly motivated and successful individual with a background in cancer genomics or bioinformatics. The Schultz lab is part of the Computational Oncology Service in the Department of Epidemiology & Biostatistics as well as the Center for Molecular Oncology. The lab focuses on identifying the genomic alterations that underlie different types of cancer. By applying existing and novel computational methods to large scale cancer genomics data sets, the lab aims to better understand the complex mechanisms at the gene and at the pathway level that drive tumor initiation, progression and response to therapy, with the ultimate goal of identifying targeted therapeutic options for cancer patients. A new, additional focus of the lab is the systematic extraction and standardization of clinical data elements from electronic health records. The lab is also involved in collaborative large-scale projects such as the NCI’s Center for Cancer Genomics (CCG) Genomic Data Analysis Network (GDAN), The Cancer Genome Atlas (TCGA), AACR Project GENIE, and the Human Tumor Atlas (HTAN). The group also has a strong interest in enabling discoveries by developing novel computational methods and databases that help bridge the divide between computer scientists on one side and clinicians and researchers on the other. Examples of these include the cBioPortal for Cancer Genomics, a popular resource for the visualization and analysis of cancer genomics data, and OncoKB®, a precision oncology knowledgebase.
Our group is highly collaborative, both within MSK and outside. The candidate will become part of a diverse, multicultural and multi-disciplinary team of students, postdocs and staff scientists in our research group, the cBioPortal and OncoKB® teams, as well as partner labs in Computational Oncology, the Center for Molecular Oncology, and the Human Oncology and Pathogenesis Program (HOPP). The candidate will need to interact with clinical collaborators across the hospital and will have access to large scale tumor sequencing data generated through the MSK clinical sequencing effort (MSK-IMPACT), which provides an exceptional opportunity to develop decision support tools that can be applied in clinical care. The work will combine genomic data from >70,000 tumor samples, along with treatment and outcome data mined from the electronic health records.
- Clinical outcome analysis in individual tumor types using genomic alteration and clinical data
- Identification of novel genomic variants, including those mediating treatment resistance
- Development of machine learning methods to guide treatment of cancer patients based on clinical and genomic characteristics
The ideal candidate should have:
- A Ph.D. in genetics, molecular biology, bioinformatics, statistics, computer science, or similar
- A strong background in molecular biology
- Experience in coding
- Excellent oral and written communication skills
- Collaborative skills and the ability to work in a team
- Ability to perform self-directed and guided research
Please send CV, a letter outlining your interest and names/contact information of three references via email to:
MSK is an equal opportunity and affirmative action employer committed to diversity and inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration without regard to race, color, gender, gender identity or expression, sexual orientation, national origin, age, religion, creed, disability, veteran status or any other factor which cannot lawfully be used as a basis for an employment decision.
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