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Postdoc Single Cell Rna Sequencing Analysis Jobs in Connecticut

Research experience in tRNA, RNA biology and/or RNA modifications field. * Prior experience with data analysis software (e.g. Prism) and statistics. * Experience with mammalian cell line engineering ...

Research experience in tRNA, RNA biology and/or RNA modifications field. * Prior experience with data analysis software (e.g. Prism) and statistics. * Experience with mammalian cell line engineering ...

Research experience in tRNA, RNA biology and/or RNA modifications field. * Prior experience with data analysis software (e.g. Prism) and statistics. * Experience with mammalian cell line engineering ...

Conduct quality assurance testing, including qPCR analysis, imaging assessments, and sequencing ... RNA workflows, and NGS library preparation . * Knowledge of molecular biology, cell biology ...

The biomarker assays will involve work with protein, RNA, and exosomes from tissue, urine, blood ... Perform general biomarkers assays and analyze the data. * Clearly communicate timelines and study ...

Scientist III

Ridgefield, CT · On-site

$43 - $49.62/hr

Assists in the design and execution of non-routine experiments in the context of cell based in ... Applies basic scientific principles for study design, data analysis, and interpretation; performs ...

Showing results 21-40

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.
What are popular job titles related to Postdoc Single Cell Rna Sequencing Analysis jobs in Connecticut? For Postdoc Single Cell Rna Sequencing Analysis jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Postdoc Single Cell Rna Sequencing Analysis jobs in Connecticut look for? The top searched job categories for Postdoc Single Cell Rna Sequencing Analysis jobs in Connecticut are:
Infographic showing various Postdoc Single Cell Rna Sequencing Analysis job openings in Connecticut as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Postdoctoral Associate | Beck Lab

The Jackson Laboratory

Farmington, CT

$75K/yr

Full-time

Re-posted 21 days ago


The Jackson Laboratory rating

8.3

Company rating: 8.3 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

33rd of 120 rated laboratories


Job description

The Beck Lab is seeking an enthusiastic, independent, and highly motivated postdoctoral fellow to join our innovative research group at the Jackson Laboratory for Genomic Medicine and University of Connecticut Health Center in Farmington, CT. The Beck lab uses and develops genomic and transcriptomic techniques to identify variation within repetitive and complex regions of mammalian genomes. As a postdoctoral fellow in the Beck lab, you would lead projects examining the mechanisms and consequences of structural variants across human and mammalian organisms.

To accomplish these goals, the fellow will analyze existing genomic and transcriptomic data with computational tools to identify novel loci of interest, and will execute laboratory experiments to test the consequences of genomic variation. Fluency with multiple experimental techniques coupled with ability or a willingness to learn Python or R and common bioinformatics tools is required to carry out analyses and prepare results for publication. Experience with cell culture, and in particular iPSCs, will be beneficial for these projects.

Key Responsibilities:

  • Conduct cell culture, molecular biology and biochemistry experiments
  • Maintain lab equipment, reagents, and follow safety protocols
  • Author manuscripts and grant applications
  • Present results at lectures and conferences
  • Use bioinformatics tools to analyze genomic and transcriptomic data from human and mouse samples
  • Interpret variation, variant mechanisms, and the effect of variants on transcription
  • Contribute to project planning and implementation
  • Perform data curation and maintain documentation
  • Generate reproducible analysis and properly use statistics to support observations
  • Collaborate with a multidisciplinary team of researchers who perform bench and computational experiments

Preferred/bonus skills:

  • Experience with iPSC culture and differentiation
  • Knowledge of structural variation and variant mechanisms
  • Experience using computational libraries for tabular data and statistical analysis
  • Experience executing jobs and pipelines in a high-performance computing cluster
  • Experience working in a Linux command-line environment

Qualifications:

  • PhD in Physiology, Molecular Biology, Genetics, Biomedical Engineering, or a related field
  • Strong publication record in peer-reviewed journals
  • Excellent communication and teamwork skills, with the ability to work independently and collaboratively
  • Experience using statistical inference to support results

Application Instructions: Please submit your current CV, at least 2 letters of reference, and a 1-page (maximum) statement

JAX Salary:

Year 0 - 1: $65,589

Year 1 - 2: $67,318

Year 2 - 3: $69,095

Year 3 - 4: $70,521

Year 4 - 5: $72,877

Year 5 - 6: $75,569

Based on years of experience as Postdoc

About JAX:

The Jackson Laboratory is an independent, nonprofit biomedical research institution with a National Cancer Institute-designated Cancer Center and nearly 3,000 employees in locations across the United States (Maine, Connecticut, California),Japan andChina. Its mission is to discover precise genomic solutions for disease and empower the global biomedical community in the shared quest to improve human health.

Founded in 1929, JAX applies over nine decades of expertise in genetics to increase understanding of human disease, advancing treatments and cures for cancer, neurological and immune disorders, diabetes, aging and heart disease. It models and interprets genomic complexity, integrates basic research with clinical application, educates current and future scientists, and provides critical data, tools and services to the global biomedical community. For more information, please visitwww.jax.org.

EEO Statement:

The Jackson Laboratory provides equal employment opportunities to all employees and applicants for employment in all job classifications without regard to race, color, religion, age, mental disability, physical disability, medical condition, gender, sexual orientation, genetic information, ancestry, marital status, national origin, veteran status, and other classifications protected by applicable state and local non-discrimination laws.


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