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Postdoc Single Cell Rna Sequencing Analysis Jobs in Massachusetts

Harvard University

Postdoctoral Fellow

Cambridge, MA · On-site

$67K - $80K/yr

Position Details Title Postdoctoral Fellow School Faculty of Arts and Sciences Department/Area Stem ... generation sequencing is highly preferred. 3. Familiarity with single cell data analysis is ...

Harvard University

Research Assistant III Lab

Boston, MA · On-site

$54/hr

Analysis of nascent RNA - RNA actively being made - can reveal details of transcriptional responses ... For this reason, nascent RNA-seq methods in conjunction with Next Generation Sequencing (NGS ...

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Postdoc Single Cell Rna Sequencing Analysis information

What is the difference between Postdoc Single Cell Rna Sequencing Analysis vs Postdoc Bioinformatics?

AspectPostdoc Single Cell Rna Sequencing AnalysisPostdoc Bioinformatics
Required CredentialsPhD in Biology, Genetics, or related field; experience in sequencing data analysisPhD in Computer Science, Bioinformatics, or related field; programming skills essential
Work EnvironmentResearch labs focusing on genomics and cell biologyResearch institutions, biotech companies, or academic labs with computational focus
Employer & Industry UsageBiotech, academic research, pharmaceutical companiesBiotech, healthcare, academic research, industry R&D

Postdoc Single Cell Rna Sequencing Analysis specialists focus on analyzing single-cell transcriptomics data, often requiring biological expertise and lab experience. In contrast, Postdoc Bioinformatics roles emphasize computational skills and software development to interpret large datasets across various biological contexts. Both roles are vital in genomics research but differ in their primary focus and skill set.

What are the key skills and qualifications needed to thrive as a postdoc in single cell RNA sequencing analysis, and why are they important?

To thrive as a Postdoc in Single Cell RNA Sequencing Analysis, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by a PhD in a relevant field. Proficiency with computational tools such as R, Python, and specialized single-cell analysis platforms (e.g., Seurat, Scanpy), as well as experience with data visualization and next-generation sequencing, is essential. Strong problem-solving abilities, effective communication, and collaboration skills help distinguish top candidates in interdisciplinary research environments. These skills enable accurate data interpretation, drive innovation, and support impactful scientific discoveries in complex biological systems.

What are some common challenges faced by postdocs working in single cell RNA sequencing analysis, and how can they be addressed?

Postdocs in single cell RNA sequencing analysis often encounter challenges such as managing large and complex datasets, integrating multi-omic data, and staying current with rapidly evolving bioinformatics tools. Collaborating closely with wet lab scientists and computational biologists is essential to interpret results accurately and to troubleshoot technical issues. Building strong programming and statistical skills, as well as actively participating in lab meetings and seminars, can help address these challenges and contribute to both personal growth and successful project outcomes.

What does a postdoc in single cell RNA sequencing analysis do?

A Postdoc in Single Cell RNA Sequencing (scRNA-seq) Analysis specializes in analyzing gene expression data from individual cells. Their main responsibilities include processing raw sequencing data, performing quality control, identifying cell types or states, and interpreting biological insights from the data. They often develop or apply computational methods to handle large datasets, collaborate with experimental biologists, and present findings through publications or conferences. The ultimate goal is to understand cellular heterogeneity and uncover new biological mechanisms at the single-cell level.
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Postdoc Single Cell Rna Sequencing Analysis jobs near you

Postdoctoral Research Fellow - Multiomics

Dana-Farber Cancer Institute

Boston, MA

$72K - $76K/yr

Full-time

Posted 25 days ago

Dana-Farber Cancer Institute rating

8.1

Company rating: 8.1 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

Job description

We are seeking a highly motivated Postdoctoral Research Fellow to join the Center for Functional Cancer Epigenetics (CFCE) at Dana-Farber Cancer Institute and become part of a multidisciplinary project led by Paloma Cejas and Henry Long, in collaboration with AITIA, an artificial intelligence and computational biology company. The project focuses on understanding patient responses to drug treatments through multiomic analyses, including chromatin profiling, single-cell sequencing, and spatial transcriptomics, using samples derived directly from clinical trials. The successful candidate will work at the intersection of computational biology, genomics, epigenomics, artificial intelligence, and clinical data science, contributing to projects that leverage cutting-edge multiomic datasets to develop predictive models of therapy response and identify clinically actionable biomarkers.

Located in Boston and the surrounding communities, Dana-Farber Cancer Institute is a leader in life changing breakthroughs in cancer research and patient care. We are united in our mission of conquering cancer, HIV/AIDS, and related diseases. We strive to create an inclusive, diverse, and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.
 

Key Responsibilities:

  • Develop and implement computational pipelines for the integration of multiomic datasets, including transcriptomics, chromatin profiling, genomics, spatial transcriptomics and single-cell data.

  • Apply statistical, machine learning, and network-based approaches to analyze high-dimensional biological data.

  • Collaborate closely with experimental and clinical teams to interpret results and translate findings into actionable insights.

  • Design and optimize predictive models of drug response, including the use of digital twin simulations.

  • Assist in data visualization, interpretation, and presentation of results for publications, grant applications, and internal/external meetings.

  • Maintain rigorous documentation, reproducibility, and quality control of computational workflows.

  • Contribute to manuscript writing and dissemination of research findings.

Qualifications:

  • PhD in Bioinformatics, Computational Biology, Systems Biology, Statistics, Computer Science, or related field.

  • Strong programming skills in Python, R, or equivalent, with experience in data analysis, statistics, and machine learning.

  • Experience  with  multiomic  datasets,  including  RNA-seq,  ATAC-seq,  ChIP-seq,  spatial transcriptomics and single-cell data.

  • Familiarity with data integration frameworks, predictive modeling, and network analysis.

  • Experience with cloud computing, workflow management (Snakemake), or HPC environments is a plus.

  • Strong analytical and problem-solving skills, with attention to detail.

  • Excellent communication and teamwork skills, with ability to collaborate across experimental and computational groups.

Preferred to have:

  • Experience in translational research or working with patient-derived datasets.

  • Familiarity with chromatin biology or epigenetics.

  • Background in biomarker discovery or predictive modeling in oncology.

At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and inclusive environment where every patient, family, and staff member feels they belong. As relentless as we are in our mission to reduce the burden of cancer for all, we are committed to having faculty and staff who offer multifaceted experiences. Cancer knows no boundaries and when it comes to hiring the most dedicated and compassionate professionals, neither do we. If working in this kind of organization inspires you, we encourage you to apply.

Dana-Farber Cancer Institute is an equal opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other characteristics protected by law.  

EEO Poster.

Pay Transparency Statement

The hiring range is based on market pay structures, with individual salaries determined by factors such as business needs, market conditions, internal equity, and based on the candidate’s relevant experience, skills and qualifications.

For union positions, the pay range is determined by the Collective Bargaining Agreement (CBA).

$72,000.00 - $76,385.00

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About Dana-Farber Cancer Institute

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Dana-Farber Cancer Institute is a leader in life changing breakthroughs in cancer research and patient care. We are united in our mission of conquering cancer, HIV/AIDS and related diseases. We strive to create an inclusive, diverse, and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.

Industry

Health care and social assistance

Company size

1,001 - 5,000 Employees

Headquarters location

Boston, MA, US

Year founded

1947

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