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UMass Med School

Research Lab Tech I

Worcester, MA · On-site

$45K/yr

Under the supervision of the Principal Investigator or designee, the Research Laboratory Technician I, performs a variety of specimen preparatory techniques, dry lab data collection, and routine ...

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How much do dry lab jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for dry lab in the United States is $22.53, according to ZipRecruiter salary data. Most workers in this role earn between $18.27 and $24.28 per hour, depending on experience, location, and employer.

What skills and qualifications are needed to work in a dry lab?

To thrive as a Dry Lab Technician, you need a solid background in data analysis, computational modeling, and a relevant degree in fields such as bioinformatics, computer science, or engineering. Expertise in statistical software, programming languages (like Python or R), and familiarity with laboratory information management systems (LIMS) are typically required. Strong problem-solving skills, attention to detail, and effective communication help you interpret complex data and collaborate with multidisciplinary teams. These skills are crucial for ensuring accurate data management, insightful analysis, and successful research outcomes in a laboratory setting.

What challenges do professionals face in a dry lab environment, and how can they be addressed?

In a dry lab setting, professionals often work with computational models, simulations, and data analysis rather than wet lab experiments. A common challenge is ensuring the accuracy and reliability of simulation results, which requires strong attention to detail and robust validation against experimental or reference data. Additionally, effective collaboration with wet lab teams is essential to interpret findings and guide future research. Staying updated with the latest computational tools and best practices can help address these challenges and support successful project outcomes.

What is a dry lab?

Dry lab jobs involve computational and theoretical research, rather than traditional wet lab work with chemicals or biological samples. Professionals in dry labs use computer simulations, data analysis, and mathematical modeling to solve scientific problems in fields like physics, chemistry, or biology. These roles are essential for managing large datasets, predicting outcomes, and developing new hypotheses that can later be tested in wet labs. Common positions in a dry lab include bioinformaticians, computational chemists, and data scientists.

What is the difference between Dry Lab vs Wet Lab?

AspectDry LabWet Lab
Work EnvironmentComputer-based, simulation, data analysisPhysical experiments, chemical or biological testing
Required SkillsProgramming, data modeling, computational skillsLaboratory techniques, chemical/biological handling
Common CertificationsNone specific, often advanced degrees in science or engineeringLab safety, technical certifications
Industry UsageResearch, data analysis, computational modelingExperimental research, product development

Dry Lab roles focus on computational work, data analysis, and simulations, often requiring programming skills and advanced degrees. Wet Lab roles involve hands-on experiments and physical testing in laboratory settings. Both are essential in scientific research but differ significantly in environment and skill set.

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Infographic showing various Dry Lab job openings in the United States as of August 2026, with employment types broken down into 2% As Needed, 73% Full Time, 12% Part Time, and 13% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $46,864 per year, or $22.5 per hour.

Postdoctoral Research Associate - Geeleher Lab (dry lab)

St. Jude Children's Research Hospital

Memphis, TN • On-site

Full-time

Posted 15 days ago

St. Jude Children's Research Hospital rating

8.6

Company rating: 8.6 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

40th of 1,056 rated hospitals

Job description

The Geeleher Lab tightly integrates computational/AI-based analysis of high-throughput genomics datasets (e.g. single-cell / spatial genomics, functional screens) with wet-bench experimental work. We ultimately aim to improve outcomes for children with cancer, with a particular focus on neuroblastoma and other high-risk pediatric solid tumors. Our hybrid wet-dry lab has led publications in journals including Nature, Genome Biology, the Journal of the National Cancer Institute, and Nature Communications, and is supported by NIH funding, including R01 (NCI renewal recently scored 1st percentile) and R35 awards, as well as institutional funding from ALSAC.
We are seeking a dry-lab postdoctoral scientist to lead computational and AI/ML-driven efforts to identify therapeutic target pairs from atlas-scale pediatric single-cell and spatial transcriptomic datasets. We are particularly interested in developing AI- and agent-based approaches to nominate cell-surface antigen combinations for emerging dual-targeted and logic-gated therapeutic strategies, including AND-gated bispecific antibody-drug conjugates and logic-gated cellular therapies. Pediatric cancers are especially well suited to these approaches because many are driven by aberrant developmental or ectopic transcriptional programs that generate highly disease-selective cell states. However, systematic efforts to identify and prioritize such target pairs at scale remain very limited, creating substantial scope for discovery. Our integrated wet-dry lab is particularly well positioned to move prioritized candidates through experimental validation and preclinical development, with the goal of unlocking new therapeutic strategies for children with cancer.
Examples of recent representative papers led by dry-lab scientists in our lab (listed as first author), with strong ML/AI components include:
https://www.biorxiv.org/content/10.64898/2026.03.04.709438v2
https://link.springer.com/article/10.1186/s13059-024-03309-4
https://www.cell.com/cell-genomics/fulltext/S2666-979X(24)00368-9
https://academic.oup.com/nar/article/50/14/e80/6583238
https://www.nature.com/articles/s41467-025-66223-8
We also routinely publish tightly integrated wet-lab/computational studies, with recent first authorships by Geeleher Lab members, including:
https://www.nature.com/articles/s41467-021-26640-x
https://www.nature.com/articles/s41467-023-43134-0
https://www.nature.com/articles/s41467-025-57185-y
The candidate will be strongly supported in their career objectives, regardless of whether their goals are academic or industry, and will be supported in writing grants/fellowships if they are interested in the academic faculty path.
This position is located in Memphis, TN (100% on-site position), and relocation assistance is available. Salary and benefits follow the (highly competitive) St. Jude postdoctoral compensation scale (www.stjude.org/postdoc).
Position Responsibilities:
  • Lead independent computational/AI research projects focused on identifying and prioritizing candidate targets for emerging bispecific therapeutic strategies in pediatric cancers.
  • Develop AI and agent-based workflows integrating large-scale single-cell, spatial transcriptomic, bulk genomic, functional-genomic, and pharmacologic datasets to nominate disease-selective vulnerabilities and target combinations.
  • Nominate disease-selective cell-surface antigens and antigen combinations based on malignant-cell specificity, co-expression, spatial localization, normal-tissue expression, targetability, and therapeutic rationale.
  • Work closely with wet-lab scientists to design follow-up validation studies and interpret experimental results in the context of large-scale datasets.
  • Generate publication-quality analyses, figures, and visualizations, and contribute to study design, data interpretation, and project strategy.
  • Lead projects toward publication, including drafting manuscripts, preparing methods and results sections, and responding to reviewer comments.
  • Present research findings at lab meetings, institutional seminars, collaborative meetings, and scientific conferences.
  • Mentor junior lab members and contribute to a collaborative wet-dry lab environment.

Special Skills, Knowledge, and Abilities:
  • Strong background in quantitative/computational biology or a related field.
  • Very strong commitment to rigor and scientific integrity.
  • Proficiency in a major programming language used for data analysis, such as R or Python.
  • Experience with single-cell or spatial transcriptomic analysis is desirable.
  • Experience with machine learning, LLMs, AI agents, multimodal data integration, or automated biological interpretation workflows is desirable but not required.
  • Ability to rapidly learn, optimize, and implement new or advanced techniques as required by the evolving research direction.
  • Experience leading or substantially driving a complex research project (evidenced by e.g. a first author paper or similar tangible contribution).
  • Scientific writing skills, including experience contributing to or drafting manuscripts.
  • Experience in pediatric cancer is desirable but not required.
  • Strong written and spoken English, presentation, and communication skills.

Minimum Education and/or Training:
  • Ph.D. degree or equivalent in Computational Biology, Genetics/Genomics, Bioinformatics, Computer Science, Mathematics, Physics, or related field.

St. Jude is an Equal Opportunity Employer
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St. Jude Children's Research Hospital does not accept unsolicited assistance from search firms for employment opportunities. Please do not call or email. All resumes submitted by search firms to any employee or other representative at St. Jude via email, the internet or in any form and/or method without a valid written search agreement in place and approved by HR will result in no fee being paid in the event the candidate is hired by St. Jude.

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