POSITION: Computational Biology Research Assistant
Brown Laboratory Immune-Oncology Division, Human Oncology and Pathogenesis Program Department of Pediatrics, Memorial Sloan Kettering Cancer Center (MSK)
Lab website: www.thebrownlaboratory.com
Work in the Brown laboratory addresses how the tissue microenvironment and microbiota shape immune development using state-of-the art single cell genomics and computational approaches to dissect immune cell heterogeneity and differentiation. Recent work from the lab defined the cell types and mechanisms that instruct peripheral regulatory T cell development and tolerance to the gut microbiota (https://www.nature.com/articles/s41586-022-05309-5). Work in the lab transitions between mechanistic studies in experimental models and translational human immunology studies, with clinical collaborations at Memorial Sloan Kettering Cancer Center (MSK) and Hospital for Special Surgery.
We are seeking a highly motivated and detail-oriented individual to join our team as a Computational Biology Research Assistant. The successful candidate will be responsible for performing computational analyses on large-scale biological datasets to help drive our research efforts and will work alongside a highly collaborative team of dynamic and vibrant research scientists.
The Brown Lab is located in the state-of-the art Zuckerman Research Center, in the heart of the Upper East Side, New York City. The ZRC is embedded in the Tri-Institutional Campus, encompassing Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, and Rockefeller University. The research assistant will be part of this dynamic community of scientists with frequent networking and career development opportunities. Dr. Brown is a physician scientist and Assistant Attending in the Department of Pediatrics. MSK is one of the world’s premier cancer centers, committed to exceptional patient care, leading-edge research, and superb educational programs.
Dr. Chrysothemis Brown is an Assistant Member, MSK, and Assistant Professor, Weill Cornell Graduate School of Medical Sciences. Dr. Brown received the NIH/NIAID DP2 New Innovator Award, Josie Robertson Investigator Award, and V Foundation Pediatric Scholar Award. As a Parker Senior Fellow, Dr. Brown is also supported by the Parker Institute for Cancer Immunotherapy.
Responsibilities:
• Work collaboratively with research scientists to design and implement computational workflows for analyzing large-scale biological data sets.
• Perform quality control on raw data generated by experiments and preprocess data for downstream analyses.
• Utilize various bioinformatics tools and software to analyze and interpret high-throughput sequencing data, including single cell RNA-seq, scATAC-seq, CUT&Tag.
• Apply statistical methods and machine learning algorithms to identify patterns and relationships in large and complex data sets.
• Communicate effectively with team members and provide clear and concise reports and summaries of data analyses.
Requirements:
• Bachelors or Masters degree in Bioinformatics, Computational Biology, or a related field.
• Strong programming skills in Python or R
• Experience with data analysis and visualization software
• Familiarity with commonly used bioinformatics tools and databases
• Excellent analytical and problem-solving skills.
• Strong communication and interpersonal skills.
APPLICATION PROCESS
Interested applicants should send the following materials, preferably as a single PDF file, by email to Dr. Chrysothemis Brown (brownc10@mskcc.org):
• Cover letter indicating current and future research interests
• CV (including list of publications and technical skills)
• Names and contact information of at least 2 references.
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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