Job:Postdoctoral Researcher in Cancer Biology and Genomics (Boston)
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3.2 years ago
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Postdoctoral Researcher in Cancer Biology and Genomics

About us

The Dries lab is a young and dynamic research group at Boston University Medical Center in the department of Hematology and Medical Oncology and Computational Biomedicine, also affiliated with the Center of Regenerative Medicine (CReM). The lab is establishing a unique research program that couples advanced genomic technologies with the development of novel multi-cellular cancer models. The lab is particularly focused on studying how cancer development and progression are steered by the tumor microenvironment and how this contributes to the observed cellular heterogeneity and epigenetic plasticity in cancer cells. We aim to leverage this information to identify and target novel vulnerabilities in cancer cells and their supporting environment.

Candidate profile

We are seeking individuals with a passion for fundamental science, interested in conducting high impact cancer research. Candidates will explore and establish multicellular cancer models, be involved in the generation of novel hypotheses and test these using a combination of such experimental cancer models and state-of-the-art genomic datasets.

Research interests in the Dries lab include:

  • Spatial transcriptomics and multiplexed imaging to explore factors of spatial variation
  • Dissecting mechanisms of cell to cell communication
  • Single-cell analysis to dissect tumor heterogeneity
  • Generation and integration of multi-omics datasets:
    • Nascent transcription
    • Epigenetics
    • DNA replication
    • Chromatin organization
  • Developing novel computational methods and tools

Candidates with strong interest and/or expertise in any of these research areas are highly encouraged to apply. Candidates with a background in cell and molecular biology and a strong determination to learn computational biology and data analysis will also be considered. This position offers a mix of experimental wet lab experience and computational analysis and the ideal candidate is enthusiastic about exploring and combining both. The exact balance of the two can be tailored to a candidate’s unique interests and skill set.


Experience in one or more of the following qualities is considered a plus:

  • PhD in computational biology, genomics, genetics, molecular biology or a relevant field
  • Experience with analyzing complex datasets, ideally next-generation sequencing, transcriptomic or (epi-)genomic data
  • Experience with scientific programming (such as R, Bash, Python, or C/C++), data analyses and data visualization
  • Fluency in Unix, standard bioinformatic tools, and comfortable applying relevant statistical methods
  • Good communication skills and proficiency in English (both with respect to presentation and writing skills)
  • Self-motivated and enthusiastic to work in an interactive, diverse and international research environment, ability to work independently and as part of a team

Our offer

We offer you a cutting-edge, interdisciplinary research project using data from state-of-the-art multi-omics technologies in a fruitful, collaborative research environment. Three cornerstone values drive BMC's pursuit to deliver exceptional care without exception, guiding our beliefs, behaviors, and decision making along the way. In the same spirit, we strive for gender and diversity equality and highly encourage applications from underrepresented backgrounds. The position is available immediately and funding is available for at least two years.


Ruben Dries, Ph.D
Assistant Professor of Medicine
Divisions of Hematology and Oncology and Computational Biomedicine
Associate Member, Center for Regenerative Medicine (CReM)
Boston University School of Medicine
650 Albany St., 4th Floor Boston, MA 02118


Please send your full application as a PDF to The application should include a cover letter, detailed CV, a description of research experience and interests (1-2 pages max) and contact details for two references. Please also indicate a preferred starting date.

Spatial Genomics R Cancer Single-Cell • 1.4k views

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