Institute for Genomic Health at the Icahn School of Medicine at Mount Sinai
Location: New York, New York
Type: Full Time
Years of Experience:
2 - 4
2 openings available.
Telecommuting is allowed.
Mount Sinai, located in New York City, NY, is seeking an exceptional and motivated Bioinformatician with expertise in computational genomics and/or statistical genetics to support projects in the Institute for Genomic Health (IGH) at the Icahn School of Medicine at Mount Sinai in New York City. IGH is empowering multi-disciplinary research to accelerate the translation of insights from massive-scale genomic databases into routine clinical care for the benefit of patients from diverse populations. We seek a bioinformatician interested in working in a fast-paced, highly collaborative environment with interdisciplinary teams of genetic researchers, clinician scientists, data scientists, and disease area experts. The individual will demonstrate strong statistical and computational genomics programming proficiencies with proven expertise in genomic analysis and advanced knowledge of analytical methodologies.
Additionally, through the newly launched Mount Sinai Million Health Discoveries Program, which aims to enroll one million racially and ethnically diverse patients in the next five years, we plan to advance precision medicine research and improve patient care. This position offers a unique opportunity to develop and lead genomic research using cutting edge health systems data.
Roles & Responsibilities:
Performs statistical genetics analysis of large-scale datasets of human germline genomic datasets (genome sequencing and array) linked to patient health records to support genomic discovery and genomic risk prediction
Generates analytical pipelines, tools, and best practices for genomic discovery in diverse and admixed populations
Documents analyses, creates summaries, and presents written and verbal results to requestors.
Writes text for study reports and Prepares analysis plans and methods used for incorporation in abstracts, manuscripts, and grants.
Identifies potential data problems from analytic queries and takes appropriate actions to guide the resolution
Collaborates with principal investigators, co-investigators, sponsors, and external representatives to ensure that project results and conclusions are presented accurately and without bias and to jointly achieve objectives and
Provides consultation to the clinical research project team on statistical issues related to the project.
Supports the clinical research team to identify potential data problems from analytic queries and to take appropriate action to guide the resolution
Performs other related duties as
Strength Through Diversity
The Mount Sinai Health System believes that diversity and inclusion is a driver for excellence. We share a common devotion to delivering exceptional patient care. Yet we’re as diverse as the city we call home- culturally, ethically, in outlook and lifestyle. When you join us, you become a part of Mount Sinai’s unrivaled record of achievement, education, and advancement as we revolutionize healthcare delivery together. We work hard to recruit and retain the best people, and to create a welcoming, nurturing work environment where you have the opportunity and support to develop professionally. We share the belief that all employees, regardless of job title or expertise, have an impact on quality patient care.
Who We Are
Over 42,000 employees strong, the mission of the Mount Sinai Health System is to provide compassionate patient care with seamless coordination and to advance medicine through unrivaled education, research, and outreach in the many diverse communities we serve.
Formed in September 2013, The Mount Sinai Health System combines the excellence of the Icahn School of Medicine at Mount Sinai with seven premier hospital campuses, including Mount Sinai Beth Israel, Mount Sinai Beth Israel Brooklyn, The Mount Sinai Hospital, Mount Sinai Queens, Mount Sinai West (formerly Mount Sinai Roosevelt), Mount Sinai Morningside (formerly Mount Sinai St. Luke’s), and New York Eye and Ear Infirmary of Mount Sinai.
The Mount Sinai Health System is an equal opportunity employer. We comply with applicable Federal civil rights laws and does not discriminate, exclude, or treat people differently on the basis of race, color, national origin, age, religion, disability, sex, sexual orientation, gender identity, or gender expression.
MS in Bioinformatics, Computer Sciences, Statistics or related PhD in related field preferred.
4 years of experience in research environment, including 2 years, manipulating large genomic
Advanced knowledge of genetics and/or statistics analysis software and online Experience in programming environments such as R statistical package, Python, BioConductor etc.
Good organization and communication skills, with demonstrated ability to productively work as a member of a team. Strong verbal and written communication skills in English are required. Experience analyzing high-throughput genomic
Interested candidates should send a CV and cover letter to Project Manager Lisa Wang at [email protected]Review of applications will begin immediately and will remain open until the position is filled.
About Institute for Genomic Health at the Icahn School of Medicine at Mount Sinai
The Institute for Genomic Health is committed to accelerating the integration of genomic information into clinical care throughout the Mount Sinai Health System. Investigators at the Institute are leading international collaborations that harness the power of massive-scale genomics research to bring new discoveries to the front line of clinical care for use in diagnosis and preventive health. In the next decade, the routine care of patients will increasingly be centered on genomic information. The rich scope of genetic, demographic, clinical, and lifestyle data in our health system is accelerating the pace at which we are discovering genetic variants that impact disease. Our research helps translate these findings into medical knowledge that can be used to predict, diagnose, or even prevent disease. Our faculty include experts in computer science, genomics, and medicine.