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Bioinformatics Machine Learning Jobs in Saint Louis, MO

Post Doctoral Fellow

Saint Louis, MO · On-site

$47K - $64K/yr

Develop and apply statistical and machine-learning models (e.g., mixed-effects models, survival ... PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, Systems Biology, or a ...

Bioinformatics Machine Learning information

See Saint Louis, MO salary details

$57.8K

$91.8K

$145.3K

How much do bioinformatics machine learning jobs pay per year?

As of Aug 23, 2026, the average yearly pay for bioinformatics machine learning in Saint Louis, MO is $91,850.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,600.00 and $125,900.00 per year, depending on experience, location, and employer.

What is a bioinformatics machine learning?

A Bioinformatics Machine Learning job involves applying machine learning techniques to analyze and interpret biological data, such as genomics, proteomics, and medical records. Professionals in this field develop algorithms, build predictive models, and enhance data-driven research in areas like personalized medicine and drug discovery. They work with large datasets, applying deep learning, neural networks, and other AI methods to extract meaningful insights. The role requires expertise in biology, statistics, and programming languages like Python or R.

What are the typical daily responsibilities for someone in a bioinformatics machine learning position?

In a Bioinformatics Machine Learning role, your daily tasks usually involve developing and tuning machine learning models to analyze large biological datasets, such as genomics or proteomics data. You'll collaborate closely with researchers, biologists, and data scientists to understand project goals, interpret results, and refine analytical approaches. Routine work includes coding, troubleshooting algorithms, visualizing data outputs, and documenting findings for internal teams or publication. The role often requires balancing independent analysis with teamwork and regular communication across disciplines, making it both technically challenging and highly collaborative.

What are the key skills and qualifications needed to thrive in the bioinformatics machine learning position, and why are they important?

A successful Bioinformatics Machine Learning professional needs a solid background in biology, statistics, and computer science, often backed by an advanced degree such as a Master's or PhD in bioinformatics, data science, or a related field. Proficiency with programming languages like Python or R, experience with machine learning libraries (e.g., TensorFlow, scikit-learn), and knowledge of version control systems are typical requirements, and relevant certifications can be beneficial. Strong problem-solving abilities, effective communication skills, and the capacity to work collaboratively in interdisciplinary teams set candidates apart. These skills are crucial for designing robust computational models, interpreting complex biological data, and translating findings into actionable insights in research or clinical settings.

Do bioinformatics machine learning professionals make a lot of money?

Bioinformatics machine learning professionals often earn competitive salaries due to the specialized skills in data analysis, programming, and biological sciences. Salaries vary based on experience, education, and location, but professionals in this field typically have higher earning potential compared to many other biotech roles. Advanced knowledge of tools like Python, R, and machine learning frameworks can also influence compensation levels.

What are the most commonly searched types of Bioinformatics Machine Learning jobs in Saint Louis, MO?

The most popular types of Bioinformatics Machine Learning jobs in Saint Louis, MO are:

What are popular job titles related to Bioinformatics Machine Learning jobs in Saint Louis, MO?

For Bioinformatics Machine Learning jobs in Saint Louis, MO, the most frequently searched job titles are:

What job categories do people searching Bioinformatics Machine Learning jobs in Saint Louis, MO look for?

The top searched job categories for Bioinformatics Machine Learning jobs in Saint Louis, MO are:

Infographic showing various Bioinformatics Machine Learning job openings in Saint Louis, MO as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $91,850 per year, or $44.2 per hour.

Post Doctoral Fellow

Saint Louis University

Saint Louis, MO • On-site

$47K - $64K/yr

Full-time

Re-posted 16 days ago


Saint Louis University rating

8.9

Company rating: 8.9 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

34th of 622 rated colleges and universities


Job description

Who is Saint Louis University? Founded in 1818, Saint Louis University is one of the nation's oldest and most prestigious Catholic universities. SLU, which also has a campus in Madrid, Spain, is recognized for world-class academics, life-changing research, compassionate health care, and a strong commitment to faith and service.
Postdoctoral Fellow - Computational Biology / Bioinformatics
Focus: Multi-omics and Longitudinal Modeling in Alzheimer's Disease
Appointment: Full-time, 1-year term (renewable pending funding and performance)
Position Overview
We are seeking a highly motivated Postdoctoral Fellow with a PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, or a related quantitative field to join an interdisciplinary research program focused on Alzheimer's disease (AD) and neurodegeneration.
The fellow will lead and contribute to advanced bioinformatics, multi-omics integration, and statistical modeling efforts using large, well-phenotyped longitudinal datasets (e.g., proteomics, transcriptomics, imaging, clinical, and biomarker data). The position is ideal for a candidate interested in mechanistic discovery, biomarker development, and translational neuroscience, with opportunities for high-impact publications and grant development.
Key Responsibilities
  • Perform computational analysis of large-scale omics datasets, including proteomics, transcriptomics, and related modalities
  • Integrate multi-omics data with clinical, cognitive, and imaging phenotypes in longitudinal cohorts
  • Develop and apply statistical and machine-learning models (e.g., mixed-effects models, survival analysis, dimensionality reduction, clustering, trajectory modeling)
  • Lead reproducible analysis pipelines in R, Python, or related frameworks
  • Interpret results in biological and clinical context, with emphasis on Alzheimer's disease mechanisms and biomarkers
  • Prepare figures, tables, and methods for peer-reviewed manuscripts and conference presentations
  • Collaborate with clinicians, wet-lab scientists, and biostatisticians in an interdisciplinary environment
  • Contribute to grant proposals and progress reports as appropriate
  • Mentor graduate or undergraduate trainees in computational methods (optional, depending on interest)

Required Qualifications
  • PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, Systems Biology, or a related quantitative discipline
  • Strong experience with high-dimensional biological data analysis
  • Proficiency in R and/or Python for statistical computing and data analysis
  • Solid foundation in statistics and data modeling, particularly for longitudinal or cohort-based data
  • Demonstrated ability to work independently and manage complex datasets
  • Strong written and verbal communication skills in English
  • Evidence of productivity (e.g., peer-reviewed publications, preprints, or advanced projects)

Preferred Qualifications
  • Experience with longitudinal modeling (e.g., mixed-effects models, disease progression modeling)
  • Familiarity with neurodegenerative disease research, Alzheimer's disease, or aging biology
  • Experience with proteomics platforms (e.g., Olink, SomaScan, mass spectrometry)
  • Knowledge of multi-omics integration, network analysis, or pathway enrichment methods
  • Experience working with large consortium datasets (e.g., ADNI, AMP-AD, UK Biobank, similar)
  • Interest in translational research, biomarker discovery, or drug target identification
  • Experience with reproducible research practices (version control, documentation, workflow tools)

Environment & Opportunities
The fellow will join a highly collaborative research environment at the interface of neurology, neuroscience, and computational biology, with access to rich datasets and strong clinical context. The position offers:
  • Intellectual ownership of projects
  • Opportunities for first-author publications
  • Exposure to grant writing and translational research strategy
  • Career mentorship tailored to academic, industry, or hybrid career paths

Term & Compensation
  • One-year appointment with possibility of renewal based on funding and performance
  • Competitive salary and benefits commensurate with experience and institutional guidelines

Application Instructions:
Applicants should submit:
1) Curriculum vitae 2) Brief cover letter describing research interests and relevant experience 3) Contact information for 2-3 references
Grant-funded Post-Doctoral appointments may be terminated if grant funding ends.
This position does not currently sponsor J1, H1B, or O visas.
Function
Research Support
Scheduled Weekly Hours:
40
Saint Louis University is an equal opportunity/affirmative action employer. All qualified candidates will receive consideration for the position applied for without regard to race, color, religion, sex, age, national origin, disability, marital status, sexual orientation, military/veteran status, gender identity, or other non-merit factors. If accommodations are needed for completing the application and/or with the interviewing process, please contact Human Resources at 314-977-5847.

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