Principal Computational Biologist, The Shah Lab at Memorial Sloan Kettering Cancer Center

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

14 Feb, 26

Salary

246300.0

Posted On

16 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Bioinformatics, Computational Biology, Data Analysis, Python, R, Linux, Git, High Throughput Sequence Data, Single Cell Genomics, Molecular Biology, Analytical Skills, Collaboration, Communication, Problem Solving, Curiosity, Resilience

Industry

Hospitals and Health Care

Description

About Us: The people of Memorial Sloan Kettering Cancer Center (MSK) are united by a singular mission: ending cancer for life. Our specialized care teams provide personalized, compassionate, expert care to patients of all ages. Informed by basic research done at our Sloan Kettering Institute, scientists across MSK collaborate to conduct innovative translational and clinical research that is driving a revolution in our understanding of cancer as a disease and improving the ability to prevent, diagnose, and treat it. MSK is dedicated to training the next generation of scientists and clinicians, who go on to pursue our mission at MSK and around the globe. Exciting Opportunity at MSK: The Shah Lab and the Department of Pediatrics are looking to hire an enthusiastic and highly motivated Senior Staff Scientist with a strong cancer genomics background. You will join an interdisciplinary team of computational scientists, molecular biologists, and clinicians working together to uncover the molecular foundations of pediatric cancers and accelerate the translation of genomic discoveries into improved treatment options. In this role, you will work directly with genomic data from patients under active treatment at MSKCC, contributing to analyses that help characterize each child’s disease in near real time. You will also play a key role in developing and applying new computational approaches to interrogate cancer genomes using state-of-the-art technologies, including single-cell and long-read sequencing. Your projects will span multiple dimensions of translational cancer genomics—from developing new approaches for disease monitoring in cell-free DNA, to investigating the mechanistic and evolutionary basis of childhood malignancies n patient-derived xenografts. This position sits at the interface of discovery-based and clinical research. Your work will contribute both to the advancement of methods that redefine how we study cancer genomes and to the translation of those insights into strategies that may improve outcomes for children with cancer. Role Overview: Collaborate with physician-scientists to analyze sequencing data from pediatric cancer patients to better understand disease progression and treatment options. Engage deeply with bulk and single-cell sequencing datasets to explore novel, clinically relevant questions. Develop computational methods to analyze data generated by groundbreaking single-cell and long-read technologies. Contribute to high impact journal articles and gain recognition through authorship. Submit abstracts and travel to conferences to present your work. Research new developments in computational biology and apply these methods to new data sets. Key Qualifications: PhD in Bioinformatics, Computational Biology, or Computer Science with emphasis on applications in molecular biology Adept with data analysis using the latest packages in Python or R Experience with Linux and the command line Familiarity with git and working collaboratively on a codebase. Experience working with high throughput sequence data. Experience with single cell genomics Core Skills: Deep curiosity about molecular and cell biology, with a strong drive to advance science and improve lives. Motivated by discovery and energized by working with complex, real-world data. Meticulous and analytical, with a knack for spotting patterns and resolving data anomalies. Collaborative and communicative, able to build strong partnerships across scientific and clinical teams. Decisive and resilient, with a proven ability to navigate challenges and keep projects moving forward. Quick to learn and apply new methods, drawing from experience to solve emerging research questions. Additional Information: Schedule: Flexible in-person, average 4 days a week onsite, 37.5 hours Location: 323 E. 61St (Macklowe) NYC Reporting to: Associate Attending This role offers a competitive salary (typically starting near the lower end of the posted range), along with an annual bonus incentive, annual merit increase, and opportunities to attend and present at leading conferences! Helpful Links: Compensation Philosophy Benefits Pay Range: $149,200.00 - $246,300.00 FSLA Status: Exempt Closing: At MSK, we believe in fair, competitive pay that reflects your job, experience, and skills. 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. Federal law requires employers to provide reasonable accommodation to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job or to perform your job. Examples of reasonable accommodation include making a change to the application process or work procedures, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. Our multi-disciplinary teams work together to provide exceptional patient care, develop innovative research, and deliver outstanding educational programs. Learn More The people of MSK make this an incredible place to work, grow and make a difference. Discover what makes us unique

Responsibilities

Collaborate with physician-scientists to analyze sequencing data from pediatric cancer patients to better understand disease progression and treatment options. Develop computational methods to analyze data generated by groundbreaking single-cell and long-read technologies.