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$56.6K

$89.9K

$142.3K

How much do bioinformatics machine learning jobs pay per year?

As of Jun 18, 2026, the average yearly pay for bioinformatics machine learning in Indiana is $89,898.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,200.00 and $123,200.00 per year, depending on experience, location, and employer.

What is a Bioinformatics Machine Learning job?

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.

What are the most commonly searched types of Bioinformatics Machine Learning jobs in Indiana? The most popular types of Bioinformatics Machine Learning jobs in Indiana are:
What are popular job titles related to Bioinformatics Machine Learning jobs in Indiana? For Bioinformatics Machine Learning jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Bioinformatics Machine Learning jobs in Indiana look for? The top searched job categories for Bioinformatics Machine Learning jobs in Indiana are:
Bioinformatics Machine Learning jobs near you
Computational Chemistry/Toxicology Scientist

Computational Chemistry/Toxicology Scientist

Vish Consulting Services Inc

Zionsville, IN • On-site

Contractor

Posted 24 days ago

Job description

VCS is looking for a computational chemistry/Toxicology Scientist for one of our client

Job Title - Computational Chemistry/Toxicology Scientist

Job Location - Indianapolis, IN 46077

Contract- 12+ Months with possible extension

Shift- Day M-F 40 hrs./week

Pay- 57/Hr.

Description:
The client has an exciting and challenging opportunity in the Predictive Safety Center within Regulatory Science for a Computational Scientist Contractor with expertise in c/Bioinformatics. The individual will partner with a multidisciplinary team to design, develop, and implement machine learning models to predict safety profiles of chemicals to support the discovery, development and registration of novel crop protection products. This position is located in Indianapolis, IN, while strong candidates working remotely will be considered.
Responsibilities:

  • Develop and apply chemistry structure-based predictive models for assessing safety profiles of early-stage discovery molecules
  • Assess potential mechanisms of toxicity by assessing ligand-protein binding affinity using protein structure alignment, binding pocket evaluation, and molecular docking
  • Work collaboratively with internal and external cross-functional multidisciplinary teams, collaborators, and consultants to implement in silico models to meet business needs
  • Serve as a subject matter expert on in silico modelling for the team and other partners in R&D sub-functions
  • Present the development and application of cheminformatics/bioinformatics approaches and novel ML/DL models internally and externally including scientific conferences
  • Keep abreast of the latest scientific development in the areas of machine learning, cheminformatics, bioinformatics, and related fields and identify technologies to be applied internally
  • Analyze complex datasets using machine learning approaches and interpret results to improve data-driven decision-making processes

Qualifications:

  • Ph.D. degree in Cheminformatics, Computational Chemistry, Computational Biology, Bioinformatics, Toxicology, or a related field
  • 3+ years of experience in developing machine learning models and applying cheminformatics/bioinformatics and AI for structure-based drug design, toxicology assessment, mechanism prediction
  • Strong technical background in machine learning, deep learning, and statistical modeling with prior experience in applying these techniques to process, analyze and draw insights from complex datasets involving chemical compound structures and toxicity endpoints
  • Demonstrated programming proficiency in Python and experience in utilizing machine learning libraries
  • Demonstrated in-depth knowledge in toxicology, chemistry, chemical structure, QSAR, protein structure
  • Knowledge in omics analysis and systems biology is a plus
  • Demonstrated teamwork and project leadership skills to manage multiple projects on different timelines for stakeholders across the business
  • Excellent communication and presentation skills to different stakeholder audiences

Thank You!

Bhanendra S Singh
Vish Consulting Services(VCS)
Bhanendra @vishusa.com