Post Doctoral Research Trainee – Computational Cancer Genomics

Job Title: Post Doctoral Research Trainee – Computational Cancer Genomics

Job Number: 57695

Location: Manhasset, NY, US

Job Description

Position Summary

The Translational Health Disparities Lab at the Institute of Molecular Medicine, Feinstein Institutes for Medical research is seeking a highly skilled and experienced quantitative scientist with expertise in cancer genomics and a passion for health equity.

The long-term research goal of the lab is to understand the genetic and biological factors that determine racial and ethnic cancer disparities. We seek to understand how genetic variation interacts with environmental factors to influence molecular phenotypes that lead to disease. We are particularly interested in developing a mechanistic understanding of the genetic and biological basis of race and ethnicity-based disparities in cancer etiology, incidence, and outcomes.

The successful candidate will be responsible for performing investigative research by developing and implementing computational solutions for analyzing large-scale genomics data from diverse populations, with a focus on understanding cancer health disparities. They will collaborate with other research staff and publish and present data in a timely manner. They will also work collaboratively with other investigators to facilitate their scientific research and training and may apply for grant funding and/or patents as appropriate. They will participate in various types of institute and community activities.

Responsibilities

•  Develop, implement and document computational solutions for analyzing large-scale high throughput sequencing data
• Conduct statistical analyses to identify patterns, correlations, and relationships in the data
• Develop and apply algorithms and software tools for data analysis and visualization
• Use AI/machine learning techniques to analyze and interpret complex biological data
• Use SQL skills to access and integrate data from multiple sources, including genomics databases, electronic medical records, and other health-related data
• Use HPC and/or cloud computing resources to accelerate data processing and analysis
• Interpret and present data to research team(s) in a clear and concise manner
• Submit manuscripts and abstracts for publication to peer reviewed journals and presentations at local, national and international scientific conferences
• Provide technical direction to research staff.

Qualifications

• Doctorate degree in Computational Biology, Bioinformatics, Computer Science, Statistics, or a related field (Ph.D. required)
• 0-2 years of relevant experience, required.
• Strong programming skills in languages such as bash, Python, R, Perl, or Java
• Demonstrable publication record with authored/co-authored publications and/or abstracts
• Excellent communication and interpersonal skills, with a demonstrated ability to work in a team environment

Preferred Qualifications and Experience

• Demonstrated ability to develop and implement novel algorithms and software tools for analysis of high-throughput sequencing datasets
• Strong SQL skills and experience in working with complex databases and large datasets
• Experience with HPC and/or cloud computing resources, such as SLURM, LSF, or AWS, and the ability to optimize computational workflows to run on these resources
• Knowledge of cancer genomics data resources such as TCGA, CCLE, and CPTAC, and the ability to mine these resources to inform analyses and develop new methods
• Use knowledge of cancer data resources to inform analyses and develop new methods for mining these resources
• Experience with commonly used data analysis and visualization tools focused on omics data

We offer a competitive salary, comprehensive benefits package, and opportunities for professional development and advancement. If you meet the above qualifications and are interested in this exciting opportunity, please submit your CV/resume and a cover letter Dr. Nyasha Chambwe explaining your interest and qualifications for the position. Please include the position title in the job header.

Application Deadline: 2023-12-31