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Postdoc Single Cell Rna Sequencing Analysis Jobs in Massachusetts

Predicta Biosciences

R&D Scientist

Cambridge, MA · On-site

... sequencing and single-cell RNA-seq. The ideal candidate has a strong technical background in ... Plan and execute experiments independently, analyze data (FlowJo for flow; and standard NGS QC ...

PREDICTA BIOSCIENCES INC

R&D Scientist

Cambridge, MA · On-site

... sequencing and single-cell RNA-seq. The ideal candidate has a strong technical background in ... Plan and execute experiments independently, analyze data (FlowJo for flow; and standard NGS QC ...

Predicta Biosciences

R&D Scientist

Cambridge, MA · On-site

... sequencing and single-cell RNA-seq. The ideal candidate has a strong technical background in ... Plan and execute experiments independently, analyze data (FlowJo for flow; and standard NGS QC ...

AA2IT

Bioinformatics Scientist - II

Cambridge, MA

$75/hr

Experience: * 5+ years of hands-on experience in multi-omics data analysis and integration. * Proven work with RNA-Seq, single-cell RNA-Seq, genotype data, spatial transcriptomics, and proteomics (e ...

AA2IT

Bioinformatics Scientist - II

Cambridge, MA

$75/hr

Experience: * 5+ years of hands-on experience in multi-omics data analysis and integration. * Proven work with RNA-Seq, single-cell RNA-Seq, genotype data, spatial transcriptomics, and proteomics (e ...

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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

Data Scientist - Computational Biology

Penfield Search Partners

Waltham, MA • Hybrid

$63K - $64K/yr

Full-time

Posted 22 days ago

Job description

Job Description Contact: Neisha Camacho/Terra Parsons - teamnt@penfieldsearch.com No 3rd party candidates Location: Waltham, MA (Hybrid - 4 days onsite/week) Penfield Search Partners is partnering with an innovative biotechnology company to identify a Data Scientist - Computational Biology contractor for a six-month assignment. This individual will support drug discovery research by processing, analyzing, visualizing, and interpreting next-generation sequencing (NGS) datasets, with a strong emphasis on transcriptomics and long-read sequencing technologies. The ideal candidate has hands-on experience with RNA sequencing data, strong computational biology expertise, and enjoys collaborating closely with experimental scientists to generate biological insights that advance therapeutic discovery

Key Responsibilities Process, analyze, visualize, and interpret NGS datasets, including bulk RNA-seq, single-cell RNA-seq (scRNA-seq), and long-read RNA sequencing data. Perform bioinformatics analyses including quality control, sequence alignment, quantification, differential expression, isoform characterization, splicing analysis, and biological interpretation. Collaborate with cross-functional teams of experimental scientists, computational biologists, and research leaders to support target discovery and validation efforts.

Translate computational findings into meaningful biological insights that inform research decisions. Evaluate and implement new bioinformatics tools, analytical methods, and emerging technologies relevant to transcriptomics and functional genomics. Develop scripts, workflows, and analytical pipelines to support reproducible and scalable data analysis.

Contribute to study design, analytical strategy, and interpretation of research findings. Present results and communicate complex analyses clearly to technical and non-technical stakeholders. Deliver high-quality work while managing multiple priorities in a collaborative research environment.

Qualifications Education & Experience MS or PhD in Bioinformatics, Computational Biology, Systems Biology, Genomics, or a related scientific discipline. Relevant industry, academic, or postdoctoral research experience in computational biology or bioinformatics. Required Skills Hands-on experience analyzing NGS datasets, particularly: Bulk RNA-seq Single-cell RNA-seq (scRNA-seq) Long-read RNA sequencing using Nanopore (required) Experience with PacBio sequencing is a plus.

Strong understanding of transcriptomics, differential expression analysis, isoform discovery, and RNA splicing analysis. Proficiency in Python and/or R. Experience working in Linux environments and high-performance computing (HPC) or cloud platforms such as AWS.

Familiarity with genome annotation resources, biological pathway databases, and systems biology concepts. Commitment to reproducible research, documentation, and version control best practices. Preferred Experience Experience with additional functional genomics data such as ATAC-seq, ChIP-seq, or PRO-seq.

Drug discovery or biotechnology industry experience. Experience collaborating with laboratory scientists in a multidisciplinary research environment. What We're Looking For We're seeking someone who is curious, collaborative, and scientifically driven, with excellent communication skills and the ability to work closely with both computational and experimental teams.

This individual should be comfortable presenting previous research, explaining analytical approaches, and contributing to a fast-paced drug discovery environment.

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