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Transcriptomics Jobs in Arnold, PA (NOW HIRING)

Transcriptomics information

See Arnold, PA salary details

$43.6K

$181.1K

$356.1K

How much do transcriptomics jobs pay per year?

As of Aug 5, 2026, the average yearly pay for transcriptomics in Arnold, PA is $181,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,900.00 and $356,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a transcriptomics scientist, and why are they important?

To thrive as a Transcriptomics Scientist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree in a relevant field. Familiarity with next-generation sequencing (NGS) platforms, RNA-seq analysis pipelines, and programming languages like R or Python is essential. Attention to detail, problem-solving abilities, and effective communication skills set outstanding candidates apart. These competencies are vital for generating accurate transcriptomic data, interpreting complex results, and collaborating within multidisciplinary research teams.

What is transcriptomics?

Transcriptomics is the study of the complete set of RNA transcripts produced by the genome under specific circumstances or in a specific cell. It provides insights into gene expression patterns, how genes are regulated, and how cells respond to various conditions. By analyzing the transcriptome, researchers can better understand biological processes, disease mechanisms, and identify potential targets for therapy. Technologies such as RNA sequencing (RNA-seq) are commonly used in transcriptomics research.

What are some common challenges faced by professionals working in transcriptomics, and how can they be addressed?

Professionals in transcriptomics frequently encounter challenges such as handling large and complex datasets, ensuring data quality, and staying current with rapidly evolving analytical tools and technologies. Working closely with bioinformaticians and statisticians is essential for effective data analysis and interpretation. Additionally, clear communication and collaboration with wet-lab biologists and clinicians help bridge the gap between raw data and meaningful biological insights. Regular training and professional development can help transcriptomics professionals stay updated with the latest best practices and software advancements.

What is the difference between Transcriptomics vs Bioinformatics?

AspectTranscriptomicsBioinformatics
Required credentialsBachelor's or Master's in Biology, Genetics, or related fields; experience with sequencing technologiesBachelor's or Master's in Computer Science, Bioinformatics, or related fields; programming skills
Work environmentLaboratories, research institutions, biotech companiesResearch labs, biotech firms, academic institutions, data analysis centers
Industry usageGenomics, molecular biology, medical researchData analysis, software development, computational biology

While both Transcriptomics and Bioinformatics involve analyzing biological data, Transcriptomics focuses on studying gene expression profiles using sequencing technologies, whereas Bioinformatics encompasses a broader range of computational methods to analyze various biological datasets. Professionals in both fields often collaborate but have distinct skill sets and work environments.

What are popular job titles related to Transcriptomics jobs in Arnold, PA? For Transcriptomics jobs in Arnold, PA, the most frequently searched job titles are:
What job categories do people searching Transcriptomics jobs in Arnold, PA look for? The top searched job categories for Transcriptomics jobs in Arnold, PA are:
What cities near Arnold, PA are hiring for Transcriptomics jobs? Cities near Arnold, PA with the most Transcriptomics job openings:
Infographic showing various Transcriptomics job openings in Arnold, PA as of June 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 95% Physical, 2% Hybrid, and 3% Remote job distribution, with an average salary of $181,145 per year, or $87.1 per hour.

Postdoctoral Position in Skeletal Regeneration, Diabetes, and Spatial Biology

University of Pennsylvania

Penn, PA • On-site

$43K - $59K/yr

Full-time

Posted 15 days ago


University Of Pennsylvania rating

8.1

Company rating: 8.1 out of 10

Based on 81 frontline employees who took The Breakroom Quiz

154th of 614 rated colleges and universities


Job description

Description
A postdoctoral position is available in the laboratory of Dr. Dana Graves at the University of Pennsylvania's School of Dental Medicine, Department of Periodontics, to investigate a newly identified mechanism through which diabetes impairs fracture healing and to develop a locally delivered therapeutic strategy to restore skeletal repair.
The project is supported by strong preliminary evidence demonstrating that lineage-specific deletion of FOXO1 in chondrocytes or osteoblasts reverses diabetes-impaired fracture healing. We have also found that disruption of primary cilia in these skeletal lineages reproduces defining features of defective repair in diabetes. Together, these findings identify and strongly support a previously unrecognized FOXO1-primary cilia signaling axis as an important regulator of skeletal regeneration under diabetic conditions.
The successful candidate will define how diabetes-induced FOXO1 activity alters ciliogenesis, cellular differentiation, and regenerative signaling in chondrocytes and osteoblasts. The studies will integrate conditional mouse models targeting FOXO1, IFT80, and combined FOXO1/IFT80 deletion with fracture-healing models of type 1 and type 2 diabetes to establish the cellular and molecular events that impair skeletal regeneration.
A major emphasis will be resolution of the fracture-healing microenvironment at spatial and single-cell resolution. Experimental approaches will include 10x Genomics Xenium spatial transcriptomics, single-cell RNA sequencing, computational analysis using R and Seurat, histology, immunofluorescence, semi-automated image analysis, and microcomputed tomography. These complementary methods will identify lineage-specific transcriptional programs, spatially organized signaling networks, and cellular interactions that distinguish effective from impaired skeletal repair and determine how these programs are altered by diabetes, FOXO1 activity, and loss of primary cilia.
The project also includes a translational component focused on a newly developed IGF-1 mimetic-containing nanofiber hydrogel designed for controlled local delivery at the fracture site. The candidate will examine its effects on inflammation and the sequential formation of immature mesenchymal tissue, cartilage, and bone, and determine whether the hydrogel restores cilia-dependent regenerative signaling, limits pathological FOXO1 activity, and improves structural and functional fracture healing in type 1 and type 2 diabetes. This work directly connects discovery of a previously unexplored regulatory pathway with preclinical evaluation of a locally delivered, mechanism-based therapy.
Professional Development and Research Environment
The fellow will be expected to take substantial intellectual ownership of the project, including development of experimental directions, leadership of spatial-transcriptomic and computational analyses, presentation of findings, and preparation of first-author manuscripts. The position provides multidisciplinary training at the interface of skeletal biology, diabetes, mouse genetics, spatial and single-cell genomics, computational biology, and translational biomaterials research. The fellow will receive direct scientific mentoring from Dr. Graves, regular project-based guidance, and opportunities to work with collaborators and shared-resource specialists across the University of Pennsylvania. Access to Penn core facilities and collaborative expertise will support spatial transcriptomics, single-cell genomics, imaging, histology, and quantitative analysis. Guided training in R, Seurat, and analysis of Xenium and single-cell datasets will be available to candidates who have strong experimental backgrounds but require additional computational experience. The research plan is designed to support intellectual independence, high-quality first-author publications, and development of a competitive platform for subsequent fellowship, faculty, or industry applications.
Qualifications
Applicants should hold a PhD, MD, DMD, DVM, or equivalent degree in skeletal biology, cell biology, molecular biology, bioengineering, diabetes biology, immunology, computational biology, or a related field.
Experience in one or more of the following areas is desirable: mouse genetics and disease models, bone or cartilage biology, fracture healing, spatial transcriptomics, single-cell RNA sequencing, computational analysis using R and Seurat, image analysis, molecular and cellular assays, histology, or microcomputed tomography. Candidates with strong experimental backgrounds who wish to develop expertise in osseous and regenerative biology, spatially resolved molecular analysis, and single-cell transcriptomics are encouraged to apply. Evidence of scientific rigor, clear communication, and the ability to work both independently and collaboratively will be important.
Application Instructions
Funding duration: The position if grant supported through 2028 and the PI has other grant support through 2031.
Anticipated start date: Available immediately following interviews and feedback from references.
Application materials: Please submit a curriculum vitae, a brief statement describing research experience and future interests, and the names and contact information of three references.
Contact: Jen East jeneast@upenn.edu

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About University of Pennsylvania

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The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News & World Report survey. Penn has 12 highly-regarded schools that provide opportunities for undergraduate, graduate and continuing education, all influenced by Penn's distinctive interdisciplinary approach to scholarship and learning. As an employer Penn has been ranked nationally on many occasions with the most recent award from Forbes who named Penn one of America's Best Employers By State in 2021.

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Year founded

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