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$203.5K

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How much do trainee bioinformatics jobs pay per year?

As of May 28, 2026, the average yearly pay for trainee bioinformatics in the United States is $203,468.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,500.00 and $400,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Trainee Bioinformatics, you need a solid grounding in biology, statistics, and computer science, often backed by a relevant bachelor's or master's degree. Familiarity with programming languages such as Python or R, experience with bioinformatics databases, and use of tools like BLAST or Galaxy are typically required. Strong analytical thinking, attention to detail, and effective communication help you interpret complex data and collaborate with interdisciplinary teams. These skills and qualities are essential for extracting meaningful insights from biological data and supporting scientific research.

What kinds of projects or tasks can a Trainee Bioinformatics expect to work on during their initial months?

As a Trainee Bioinformatics, you can expect to contribute to projects involving data preprocessing, quality control, and basic analysis of biological datasets, such as genomic or transcriptomic data. You will likely collaborate closely with senior bioinformaticians, biologists, and software developers, assisting with data annotation, pipeline testing, and report generation. The early stages often focus on building foundational skills in scripting (such as Python or R), using bioinformatics tools, and understanding the lab's data workflows, which sets you up for more complex analytical tasks as you gain experience.

What are Trainee Bioinformaticians?

Trainee Bioinformaticians are entry-level professionals who are learning to apply computational and statistical methods to analyze biological data, such as DNA, RNA, or protein sequences. They often work under the supervision of experienced bioinformaticians or researchers, assisting with data processing, software development, and research projects. Their role is crucial in fields like genomics, biomedical research, and pharmaceutical development, as they help make sense of complex biological information. Trainee Bioinformaticians typically have a background in biology, computer science, or a related field, and are developing their skills in programming, data analysis, and bioinformatics tools.

What is the difference between Trainee Bioinformatics vs Bioinformatics Analyst?

AspectTrainee BioinformaticsBioinformatics Analyst
Required CredentialsTypically a bachelor's degree in bioinformatics, biology, or related field; entry-levelBachelor's or master's degree; some roles prefer experience or certifications
Work EnvironmentTraining programs, internships, or entry-level positions in research labs or biotech companiesFull-time roles in research institutions, biotech firms, or healthcare organizations
Employer & Industry UsageUsed by employers for onboarding new talent or students gaining practical experienceUsed by employers for ongoing data analysis, research projects, and bioinformatics workflows

The main difference between a Trainee Bioinformatics and a Bioinformatics Analyst is experience level and responsibility. Trainee Bioinformatics roles are designed for individuals starting their careers, focusing on learning and skill development. Bioinformatics Analysts are more experienced professionals responsible for analyzing biological data, interpreting results, and supporting research projects.

More about Trainee Bioinformatics jobs
What cities are hiring for Trainee Bioinformatics jobs? Cities with the most Trainee Bioinformatics job openings:
What are the most commonly searched types of Bioinformatics jobs? The most popular types of Bioinformatics jobs are:
What states have the most Trainee Bioinformatics jobs? States with the most job openings for Trainee Bioinformatics jobs include:
What job categories do people searching Trainee Bioinformatics jobs look for? The top searched job categories for Trainee Bioinformatics jobs are:
Trainee Bioinformatics jobs near you
Infographic showing various Trainee Bioinformatics job openings in the United States as of May 2026, with employment types broken down into 2% Internship, 39% Full Time, 51% Part Time, 3% Temporary, 3% Contract, and 2% Nights. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $203,468 per year, or $97.8 per hour.

Senior Computational Scientist - Furman Lab

Buck Institute

Novato, CA • On-site

$120K - $130K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted yesterday

Job description

POSITION DETAILS
Salary: $120,000 - $130,000
Start Date: January 15 – February 1, 2026
Location: Buck Institute for Research on Aging (Novato, CA) – Hybrid flexibility available
Appointment: Full-time
Note: This position is contingent upon the Furman Lab being awarded a large funded project in February 2026.
ABOUT THE FURMAN LAB
The Furman Lab integrates systems biology, causal modeling, and advanced AI/ML approaches to understand the biological mechanisms underlying aging, resilience, and physiological decline. Our work integrates large human cohorts, multi-omics data, and digital health measurements to identify actionable molecular drivers of healthspan and develop predictive, translational models. As leaders of Buck Bioinformatics and Data Science Core, we build analytical standards and frameworks that support institute-wide and multi-institutional research collaborations.
POSITION OVERVIEW
The Senior Computational Scientist will play a central role in a large funded research project focused on identifying causal drivers and mechanistic pathways underlying resilience, aging trajectories, and functional decline. This individual will design and deploy causal inference pipelines, longitudinal and multiscale temporal models, and multimodal data integration approaches connecting omics, clinical phenotypes, and wearable-derived physiological signals. The role also includes co-leading the Buck Bioinformatics and Data Science Core and mentoring 2–3 trainees across aging computational biology, systems physiology, and statistical methodology.
KEY RESPONSIBILITIES
Computational Leadership
  • Lead development of causal inference frameworks (DAG-based modeling, debiased ML, identifiability assessments) to characterize mechanistic drivers of resilience and physiological decline.
  • Build and optimize state-space, Bayesian, and Kalman filter models for longitudinal, irregularly sampled, and multiscale physiological and digital phenotype data.
  • Develop interpretable multimodal models that integrate omics datasets, biomarker panels, wearable data, and clinical outcomes.
  • Address confounding, selection bias, missingness, and temporal heterogeneity using principled statistical and computational approaches, generating translational insights to inform intervention prioritization and hypothesis testing.

Core Leadership & Mentorship
  • Co-lead the Buck Bioinformatics and Data Science Core, helping define analytical standards, workflows, reproducibility practices, and strategic priorities.
  • Mentor 2–3 trainees (postdocs, analysts, graduate students) in computational modeling, systems biology, and statistical methodology.
  • Promote best practices in documentation, reproducibility, and causal reasoning across collaborating teams.

Cross-Functional Collaboration
  • Collaborate closely with experimental scientists, clinicians, AI/ML researchers, and external partners to align modeling approaches with biological and translational objectives.
  • Communicate findings through presentations, manuscripts, data-sharing deliverables, and reporting associated with the federally funded research program.

QUALIFICATIONS
Education
  • PhD in Biostatistics, Statistics, Epidemiology (methods track), Computational Biology, Systems Biology, or a related quantitative field.

Technical Expertise
  • Strong experience in causal inference, including DAG construction, confounding structures, selection bias, and identifiability conditions; familiarity with instrumental variables and debiased/orthogonal ML frameworks.
  • Experience with longitudinal and time-series modeling, including state-space or Bayesian approaches, irregular sampling, and missing data; experience modeling circadian or physiological rhythms is highly desirable.
  • Experience working with high-dimensional biological data (e.g., multi-omics, biomarker discovery) and interpretable biological modeling approaches.
  • Judicious application of machine learning methods, including latent variable models, embeddings, and dimensionality reduction, with demonstrated judgment around when deep learning is appropriate.
  • Proficiency in R as a primary programming language, with experience usingpackages such as DoubleML, dagitty, grf, KFAS, bssm, lavaan, mgcv, survival, ranger, and torch.
  • Experience with reproducible analytical workflows and version control.

Preferred Qualifications
  • Experience with wearables, digital health, or physiological sensor data.
  • Background in survival analysis, health-outcome modeling, or time-to-event frameworks.
  • Experience with single-cell or pseudotime trajectory analysis.
  • Knowledge of aging biology, geroscience, systems physiology, or resilience science.
  • Publication record in high-impact biomedical journals.

BENEFITS
  • Comprehensive benefits package (medical, dental, vision, retirement).
  • Visa sponsorship and immigration support, if needed.
  • Access to world-class analytical infrastructure, Buck core facilities, and multi-omics platforms.
  • Opportunity to contribute to pioneering research in aging, immunology, and space biosciences.
  • $5000 relocation support

TO APPLY
Interested candidates should click the Apply button to complete the online application. Please upload both your CV and a document that includes a brief statement of your interests, plus the names/contact information of 3 references.

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