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Biomarker Discovery Jobs (NOW HIRING)

GondolaBio

Senior Biological Data Scientist

$155K - $205K/yr

Experience supporting biomarker discovery, translational research, or target identification in a biotechnology or pharmaceutical setting. * Working proficiency in Python for scientific computing and ...

BridgeBio Pharma

Senior Biological Data Scientist

Experience supporting biomarker discovery, translational research, or target identification in a biotechnology or pharmaceutical setting. * Working proficiency in Python for scientific computing and ...

New

Quanterix

VP, Research Products

Billerica, MA · On-site

Preferred : • Strong understanding of biomarker discovery, translational research, or spatial biology technologies preferred. Company : Quanterix is a biotechnology company that develops ...

Natera

OR · On-site

From building genomic foundation models to developing predictive AI platforms, our mission is to accelerate biomarker discovery, improve clinical trial design, and enable novel personalized ...

QUANTERIX CORP

VP, Research Products

Billerica, MA · On-site

$270K - $360K/yr

From discovery to diagnostics, Quanterix's ultrasensitive biomarker detection is fueling breakthroughs only made possible through its unparalleled sensitivity and flexibility. Simoa ® technology has ...

The Mind Research Network

Professor

Albuquerque, NM · On-site

The successful candidate will join a highly collaborative scientific community where research spans advanced neuroimaging, computational neuroscience, biomarker discovery, mechanistic neuroscience ...

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Biomarker Discovery information

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$49K

$203.5K

$400K

How much do biomarker discovery jobs pay per year?

As of Aug 6, 2026, the average yearly pay for biomarker discovery 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 types of teams and professionals do biomarker discovery specialists commonly collaborate with?

Biomarker Discovery specialists often work closely with cross-functional teams that include clinical researchers, bioinformaticians, statisticians, pathologists, and project managers. Collaboration is vital in designing experiments, analyzing complex data sets, and advancing candidate biomarkers from discovery through validation and clinical application. These professionals frequently attend joint meetings, share results, and contribute expertise to integrated project goals. Working in this collaborative environment helps ensure comprehensive scientific approaches and accelerates the development of meaningful diagnostic or therapeutic tools.

What is a biomarker discovery?

A Biomarker Discovery job involves identifying biological markers—measurable indicators of diseases or biological processes—that can be used for diagnosis, prognosis, or treatment decisions. Professionals in this field work with biological samples, data analysis, and validation studies to find novel biomarkers. Their work is critical for developing new diagnostic tools and improving personalized medicine approaches. Roles typically require expertise in molecular biology, bioinformatics, and clinical research.

What are the key skills and qualifications needed to thrive in biomarker discovery?

To thrive in Biomarker Discovery, candidates typically need a strong background in molecular biology, biochemistry, or pharmacology, and an advanced degree such as a PhD or MS is often preferred. Proficiency with technologies like mass spectrometry, next-generation sequencing, bioinformatics platforms, and data analysis software is crucial in this field. Strong problem-solving abilities, attention to detail, and the capacity to effectively communicate findings within multidisciplinary teams help distinguish top performers. These skills are critical for identifying, validating, and translating biological markers into clinical applications that can significantly impact patient care and drug development.

More about Biomarker Discovery jobs
What cities are hiring for Biomarker Discovery jobs? Cities with the most Biomarker Discovery job openings:
What states have the most Biomarker Discovery jobs? States with the most job openings for Biomarker Discovery jobs include:
What job categories do people searching Biomarker Discovery jobs look for? The top searched job categories for Biomarker Discovery jobs are:
Biomarker Discovery jobs near you
Infographic showing various Biomarker Discovery job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $203,468 per year, or $97.8 per hour.

Computational Biologist

Verge Genomics

San Francisco, CA • On-site, Remote

Full-time

Re-posted 4 days ago

Job description

Who We Are
Verge is transforming drug discovery by using artificial intelligence and proprietary human data to solve the biggest driver of rising drug costs: high clinical failure rates. To achieve this, we have built one of the field's largest corpuses of multi-modal patient molecular and clinical data, sourced directly from human tissue. Our team of engineers, neuroscientists, and biologists have so far delivered two drugs to clinic, discovered 282 new targets, and signed commercial partnerships worth in excess of $1.6B with Eli Lily and AstraZeneca.
Your Mission
Reporting to the Head of Product & Engineering, and working alongside Verge's platform and computational biology teams, the Computational Biologist (AI/ML) will be responsible for defining and enabling new product offerings leveraging Verge's drug discovery engine for internal stakeholders, external partners (across both pharma and AI), and customers.
Your 12 Month Outcomes
  • Work with Verge's AI partners to deliver a best-in-class biology foundation model with Verge's proprietary datasets
  • Develop a novel approach that enables a powerful new product offering (patient stratification, biomarker discovery, etc.)
  • Deliver at least two CONVERGE-powered insights projects to pharma/biotech companies
  • Build an internal agentic AI workflow that supports multi-modal biomedical reasoning and orchestration

You Will
  • Develop and evaluate cutting-edge computational methodologies integrating multi-omic datasets to develop predictive models for translational biology,
  • Lead high-impact projects that apply and adapt AI models to translational challenges in disease biology, biomarker discovery, and target exploration,
  • Lead partnerships with AI companies to co-develop next-generation foundation models for drug discovery
  • Frame biological problems in computational terms and design solutions that are biologically meaningful, interpretable, and experimentally testable,
  • Design and implement evaluation methodologies for assessing AI model capabilities relevant to biological research and applications,
  • Translate between biological domain knowledge and machine learning objectives.

Requirements
Candidates must have:
  • Either:
    • PhD in computational biology, AI/ML, applied statistics, biophysics, or,
    • MS and professional experience in relevant fields.
  • ≥5 years of experience working in applied computational biology and integration of multi-omic datasets (RNA-seq, genotyping, clinical), with ≥2 years in a startup environment,
  • ≥2 years of experience in relevant areas of translational science, demonstrating a deep understanding of target identification, biomarker discovery, and/or patient stratification,
  • Proven ability to implement, evaluate, and/or create computational methodologies that leverage machine learning, statistics, and AI for biological research and discovery,
  • Fluency with state of the art in systems biology workflows, including off-the-shelf biological databases and computational biology tools,
  • Track record of bridging biological domain knowledge with computational approaches to solve real scientific problems
  • Track record of individual innovation, with published research or shipped work influencing pharma R&D decisions
  • Experience running a significant number of end-to-end RNA-Seq data analyses (from QC, read quantification, normalization through to interpretation),
  • Excellent coding skills in Python, with experience in relevant ML/AI libraries (e.g., PyTorch, HuggingFace, scikit-learn, pandas, numpy). A demonstrable portfolio (e.g., GitHub, research code, or shared notebooks) is highly preferred,
  • Experience in building and evaluating machine learning models on biological data, ideally with transformer-based models (e.g., scGPT, Geneformer, ESM, ProtBERT), with a deep understanding of feature selection, model interpretability,
  • Professional experience with AI workflows, including natural language processing (NLP), retrieval-augmented generation (RAG), embeddings, vectorization of diverse data types, and working with large language models (e.g., GPT),
  • Demonstrated experience with model evaluation and experimental design in a scientific context, including setting up appropriate benchmarks and controls.

Finally, we seek candidates who embrace our values and way of working:
  • Ability to thrive in uncertainty with frequently changing priorities
  • Deep alignment with our values
  • A passion for making an impact on patients

Apply