Bioinformatics - Computational Biology

Memorial Sloan Kettering Cancer Center
New York City, New York (US)
$60-80,000 per year + benefits
Closing date
Apr 6, 2023
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Bioinformatics, computational biology postdoctoral fellow/scholar position is available immediately in a multidisciplinary team studying protein-protein interaction networks in disease.

The successful candidate must have the capacity to execute proficient computational analyses and troubleshoot independently, communicate effectively with collaborators, and thrive in a highly collaborative team environment. This opportunity offers the candidate to leverage skills in bioinformatics and computational biology with cutting-edge biomedical research in cancer and Alzheimer’s disease.

The position will involve the analysis of omics data through the application of best-practice bioinformatics workflows and the development of innovative data analysis and visualization methods, as required. The position will require a highly motivated bioinformatician or computational biologist to provide support for a variety of projects that build on innovative omics and wet lab methods. The role requires competency in programming languages such as Python and/or R. The individual will collaborate very closely with other bioinformaticians, and biomedical researchers to work on joint initiatives.

For publications relevant to this research please refer to:

  • Nature Reviews Cancer 2018 Sep;18(9):562-575. Adapting to stress - chaperome networks in cancer. Nature 2016 Oct 20;538(7625):397-401. The epichaperome is an integrated chaperome network that facilitates tumour survival. Nature Communications 2020 Jan 16;11(1):319. The epichaperome is a mediator of toxic hippocampal stress and leads to protein connectivity-based dysfunction. Nature Communications 2018 Oct 19;9(1):4345. HSP90-incorporating chaperome networks as biosensor for disease-related pathways in patient-specific midbrain dopamine neurons. FEBS Journal 2022 Apr;289(8):2047-2066. Disease-specific interactome alterations via epichaperomics: the case for Alzheimer's disease. Commun Biol. 2021 Nov 25;4(1):1333. Pharmacologically controlling protein-protein interactions through epichaperomes for therapeutic vulnerability in cancer. Trends Pharmacol Sci 2023 Jan;44(1):20-33. Targeting stressor-induced dysfunctions in protein-protein interaction networks via epichaperomes.

The successful candidate will preferably:

  • be a highly motivated researcher with a quantitative research background.
  • be interested in contributing to cutting-edge research focusing on the dissection of the complex PPI network changes utilizing multi-omics data (mostly epichaperomics, proteomics and transcriptomics)
  • have some experience in multivariate analysis, differential expression analysis, pathway enrichment analysis and network analysis
  • show proficiency in data wrangling using (R:dplyr/tidyverse, Python:pandas/numpy)
  • show proficiency in R, Bioconductor and data visualization tools (ggplot2, plotly, Cytoscape)
  • have some familiarity with proteomics data pipelines (DIA, DDN) and data types
  • have some experience in missing value imputations and data normalization
  • have demonstrated ability to work independently and lead projects while also collaborating and assisting the group achieve its research goals
  • have some knowledge or interest in machine learning and deep learning, working with cloud computing infrastructure


  • M.Sc or Ph.D in Bioinformatics, Computer Science, Life Sciences or related fields. An early degree in or study of biology with PhD in bioinformatics is preferred.
  • Creativity in problem solving and a team spirit
  • Good communication/written skills
  • Passion for science.
  • Ability to work towards defined goals in an efficient, safe and scientifically sound manner.

Candidates with an ability to interact well with a large interdisciplinary team are encouraged to apply.

Job Type: Full-time

Salary: $60,000.00 - $80,000.00 per year + benefits (as per level of experience and expertise)

Choosing MSK for your job and training is a wise investment in your future. Among the benefits of training with us are:

  • Excellent job prospects
  • World-class science 
  • A vibrant city and community
  • Career and professional development  
  • Housing and childcare
  • Competitive compensation and benefits


  • Self-determined schedule

Ability to commute/relocate:

  • New York, NY 10065: Reliably commute or planning to relocate before starting work

Work Location: Hybrid remote in New York, NY 10065

Written applications, including a cover letter, CV and contact details of three professional referees should be forwarded to chiosisg at


The applicant will be hired as part of the Chiosis lab at Memorial Sloan Kettering. For more information on Memorial Sloan Kettering Cancer Center and the Chiosis lab see and

Memorial Sloan Kettering Cancer Center is located in New York City, in Manhattan’s Upper East Side, adjacent to the Cornell University Weill Medical College and the Rockefeller University, and a cab drive away from New York University Grossman School of Medicine, Nathan Kline Institute, and Columbia University, Taub Institute for Research on Alzheimer’s Disease and the Aging Brain. This rich scientific environment provides many unique and unparalleled research training opportunities 


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