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Computational Spatial Transcriptomics Jobs in Halethorpe, MD

Computational Spatial Transcriptomics information

See Halethorpe, MD salary details

$39

$53

$72

How much do computational spatial transcriptomics jobs pay per hour?

As of Aug 5, 2026, the average hourly pay for computational spatial transcriptomics in Halethorpe, MD is $53.65, according to ZipRecruiter salary data. Most workers in this role earn between $45.77 and $71.83 per hour, depending on experience, location, and employer.

What are some typical challenges faced when working in computational spatial transcriptomics, and how can new team members prepare for them?

Professionals in computational spatial transcriptomics often encounter challenges related to handling and analyzing large, complex datasets that combine spatial and gene expression information. Integrating data from different technologies and ensuring data quality can be demanding, requiring strong programming skills and familiarity with bioinformatics pipelines. New team members can prepare by strengthening their skills in statistical analysis, programming languages like Python or R, and staying updated on the latest spatial transcriptomics techniques. Collaborating closely with experimental biologists and data scientists is also key to overcoming these challenges and driving successful research outcomes.

What is the difference between Computational Spatial Transcriptomics vs Computational Biologist?

AspectComputational Spatial TranscriptomicsComputational Biologist
Required CredentialsAdvanced degrees in bioinformatics, computational biology, or related fields; experience with spatial data analysisTypically a PhD or Master's in biology, bioinformatics, or related disciplines; strong programming skills
Work EnvironmentResearch labs, biotech companies, academic institutions focusing on spatial genomicsResearch institutions, biotech firms, academia working on biological data analysis
Industry UsageSpecialized in spatial transcriptomics techniques and data interpretationBroad biological data analysis across various fields

Computational Spatial Transcriptomics focuses on analyzing spatial gene expression data within tissues, requiring specialized skills in spatial data processing. In contrast, Computational Biologists work on a wider range of biological data types. While both roles involve bioinformatics expertise, the former emphasizes spatial data analysis techniques specific to transcriptomics.

What is computational spatial transcriptomics?

Computational spatial transcriptomics is a field that combines advanced computational methods with spatial transcriptomics, a technique that measures gene expression within the physical context of tissue samples. It involves processing and analyzing large datasets to map where specific genes are active within tissues, helping researchers understand how cells interact and function in their native environments. This approach is crucial for studies in developmental biology, cancer research, and neuroscience, as it provides insights into cellular organization and tissue architecture. Computational tools help extract meaningful patterns from complex data, enabling discoveries that were previously impossible with traditional methods.

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

To excel in Computational Spatial Transcriptomics, you need a strong background in bioinformatics, genomics, and statistical data analysis, typically supported by advanced degrees in computational biology or related fields. Familiarity with programming languages (such as R and Python), spatial transcriptomics platforms (like 10x Genomics Visium), and high-throughput sequencing data analysis tools is essential. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for interpreting complex datasets and collaborating with multidisciplinary teams. These competencies ensure accurate data interpretation, innovative research, and successful integration of spatial transcriptomics insights into biological and clinical applications.
What cities near Halethorpe, MD are hiring for Computational Spatial Transcriptomics jobs? Cities near Halethorpe, MD with the most Computational Spatial Transcriptomics job openings:

Assistant or Associate Professor in Cancer Genomics

University of Maryland, Baltimore

Baltimore, MD • On-site

$143K - $177K/yr

Full-time

Medical, PTO

Re-posted 19 days ago


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7.7

Company rating: 7.7 out of 10

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Job description

Job Description
The University of Maryland School of Medicine (UMSOM) invites applications for tenure-track faculty positions at the rank of Assistant Professor or Associate Professor jointly appointed between the Institute for Genome Sciences (IGS) and the Greenbaum Comprehensive Cancer Center (UMGCCC). Applicants are expected to participate in a transdisciplinary genomics and computational oncology research program. IGS will provide hybrid wet and dry laboratory space as needed. Applicants should possess demonstrated expertise in developing and applying multi-omics approaches for basic and translational cancer research. We especially encourage applicants with research programs focused on tumor evolution, subclone and mutational analysis, chromatin structure, antigen prediction, immune repertoire sequencing, or other related areas.
Qualifications
The successful candidate will hold a Ph.D., M.D., or M.D./Ph.D. in genomics, systems biology, biology, computational biology, bioinformatics, bioengineering, or a related discipline, with a strong background in analyzing and integrating tumor biology and clinical data streams. Candidates should demonstrate the potential to establish a funded research program and have a strong track record of collaborations with clinical and basic scientists. The successful candidate will be expected to engage in mentoring and teaching and contribute to the service missions of IGS and UMGCCC as well as the broader UMSOM. Primary reporting and research time will be at IGS, with translational oncology research opportunities in UMGCCC. We welcome applicants with research experience in academia, industry, or government who can bring all perspectives and expertise to our team.
About the Institute for Genome Sciences
IGS (www.igs.umaryland.edu) is a transdisciplinary research institute committed to high-impact science that advances global human health. With a collaborative faculty of over 30 investigators, IGS fosters a highly integrative research environment with expertise spanning the quantitative and data sciences, systems biology, human genomics, and microbial genomics. Faculty at IGS have access to state-of-the-art genomics resources, including PacBio, Illumina, and Oxford Nanopore sequencing platforms, as well as single-cell and spatial transcriptomics through Maryland Genomics, our high-throughput core laboratory. Faculty also benefit from advanced computational infrastructure for high-throughput genomics datasets and data infrastructure supporting numerous genomics consortia. The candidate will be encouraged to build a research program collaborating with translational and basic cancer researchers in the Greenbaum Comprehensive Cancer Center and develop close partnerships with the University of Maryland College Park and the newly formed Institute for Health Computing (www.ihc.umaryland.edu), enhancing opportunities for cross-disciplinary clinical research with the University of Maryland Medical Center.
About the Greenebaum Comprehensive Cancer Center
The University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center is a National Cancer Institute-designated comprehensive cancer center within the University of Maryland Medical Center in Baltimore, the flagship academic hospital of the University of Maryland Medical System. It offers a multidisciplinary approach to treating all types of cancer and has an active clinical and basic science research program through its relationship with the University of Maryland School of Medicine. The center is ranked among the top 50 cancer programs in the country by US News & World Report.
The salary range for this position is $143,862 to $177,330 which represents the minimum and maximum salaries for this position and is based on the University of Maryland School of Medicine's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.
UMB offers a comprehensive that prioritizes wellness, work/life balance, and professional development. This position participates in a retirement program that must be selected and is effective on your date of hire. Faculty receive a generous leave package that includes over 4 weeks of vacation accrued each year, paid holidays, personal leave, unlimited accrual of sick time, and comprehensive health insurance; professional learning and development programs; tuition remission for employees and their dependents at any University System of Maryland school.
UMB is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law or policy. If you need a reasonable accommodation for a disability for any part of the employment process, please submit an online or contact . Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this email address.
We value diversity and how it enriches our academic and scientific community and strive toward cultivating an inclusive environment that supports all employees.
To Apply:
Submit a cover letter, curriculum vitae, a description of your research program, and contact information for three references to . Review of applications will begin immediately and continue until positions are filled.

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