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Freelance Bioinformatics Machine Learning Jobs in Indiana

... bioinformatics, functional genomics, and AI/ML. Implement iterative design-test-learn and active ... Collaborate with Computational Sciences to develop machine learning models for hit expansion and ...

Senior Research Scientist

Indianapolis, IN · On-site

$94K - $120K/yr

... reviews, bioinformatics, functional genomics, and AI/ML. Implement iterative "design-test-learn ... Collaborate with Computational Sciences to develop machine learning models for hit expansion and ...

Showing results 21-26

Freelance Bioinformatics Machine Learning information

What does a freelance bioinformatics machine learning specialist do?

A Freelance Bioinformatics Machine Learning specialist applies machine learning techniques to analyze biological data, such as genomics, proteomics, and medical records, on a project-by-project basis. They typically work independently with research labs, biotech companies, or healthcare organizations to develop algorithms, build predictive models, and interpret complex biological datasets. Their work helps drive insights in areas like drug discovery, personalized medicine, and disease prediction, often leveraging tools like Python, R, and specialized bioinformatics software. As freelancers, they have the flexibility to choose projects, set their schedules, and work remotely.

What are the key skills and qualifications needed to thrive as a freelance bioinformatics machine learning specialist?

To thrive as a Freelance Bioinformatics Machine Learning Specialist, you need a strong background in biology, statistics, and programming (such as Python or R), typically supported by a relevant degree in bioinformatics, computer science, or a related field. Familiarity with bioinformatics tools (e.g., BLAST, Bioconductor), machine learning libraries (scikit-learn, TensorFlow), and experience with cloud computing platforms are highly valuable. Strong problem-solving, communication, and project management skills help distinguish top freelancers in this field. These capabilities are crucial for independently delivering accurate, actionable biological insights to clients and efficiently managing multiple projects.

What are some common challenges freelance bioinformatics machine learning professionals face when working with multiple clients?

Freelance bioinformatics machine learning professionals often encounter challenges such as managing diverse data formats, aligning project expectations, and ensuring data privacy across multiple clients. Each client may have unique datasets, varying levels of documentation, and different computational infrastructure, requiring adaptability and strong communication skills. Balancing multiple deadlines and maintaining clear, consistent reporting are also important to foster trust and long-term collaborations.

What is the difference between Freelance Bioinformatics Machine Learning vs Freelance Data Scientist?

AspectFreelance Bioinformatics Machine LearningFreelance Data Scientist
CredentialsBackground in bioinformatics, biology, or related fields; knowledge of machine learningBackground in statistics, computer science, or related fields; strong programming skills
Work EnvironmentResearch labs, biotech companies, academic projects, freelance consultingVarious industries including finance, tech, healthcare, consulting
Industry UsagePrimarily biotech, healthcare, genomics, pharmaceutical sectorsBroad industry application including finance, marketing, tech, healthcare

Freelance Bioinformatics Machine Learning specialists focus on applying machine learning techniques to biological data, often working within biotech and healthcare sectors. In contrast, Freelance Data Scientists have a broader scope, working across multiple industries with diverse datasets. Both roles require strong analytical skills and programming expertise, but their industry focus and domain knowledge differ significantly.

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 Freelance Bioinformatics Machine Learning jobs in Indiana?

For Freelance Bioinformatics Machine Learning jobs in Indiana, the most frequently searched job titles are:

What cities in Indiana are hiring for Freelance Bioinformatics Machine Learning jobs?

Cities in Indiana with the most Freelance Bioinformatics Machine Learning job openings:

Infographic showing various Freelance Bioinformatics Machine Learning job openings in Indiana as of August 2026, with employment types broken down into 62% Full Time, 25% Part Time, and 13% Contract. Highlights an 62% In-person, and 38% Remote job distribution.

Senior Research Scientist

Socket.dev

Indianapolis, IN • On-site

$120 - $190/hr

Other

Retirement, PTO

Posted 4 days ago


Job description

Your Role: Senior Research Scientist - Target Intelligence and Early Project Lead

As a Senior Scientist in the Mechanistic Biology team, you will lead novel target identification and validation across multiple animal diseases to build the drug discovery pipeline. This is a non-lab role focused on guiding cross-functional teams through early-stage drug discovery by leveraging advanced in vitro techniques, integrated AI/ML-driven platforms, and functional genomics. You will be responsible for accelerating the discovery cycle through high-throughput screening (HTS) approaches to rapidly move from Hit-to-Lead for both small molecules and biologics.

Your Responsibilities:
  • Target Identification & Discovery Innovation: Lead the identification and prioritization of novel targets using in vitro/in vivo experiments, literature reviews, bioinformatics, functional genomics, and AI/ML. Implement iterative design-test-learn and active learning cycles to optimize lead compounds and accelerate the discovery cycle.
  • Screening & Digital Discovery: Design and deploy high-throughput and multi-modal screening strategies—including biochemical, biophysical, and cellular approaches to identify novel chemical and biological starting points. Leverage AI-augmented data analysis, digital phenotyping, and digital discovery platforms to accelerate candidate identification and minimize experimental costs.
  • Cross-Functional Discovery Leadership: Guide cross-functional teams through early drug discovery from initial concept through target validation, partnering closely with Computational Sciences, Chemistry, Medicinal Chemistry, Computational Biology, Technical Development, and Preclinical Development. Collaborate with Computational Sciences to develop machine learning models for hit expansion and property prediction.
  • Target De-risking, Biomarkers & Translational Models: Develop strategies to de-risk targets and enhance commercial viability by integrating Chemistry, Manufacturing, and Controls (CMC) considerations and assessing on-target/off-target safety risks. Develop and integrate biological, AI-enabled, and imaging biomarker strategies and translational in vitro disease models, including CRISPR/Cas9-edited primary cell lines and organoids, to accelerate discovery.
  • External Partnerships & Scientific Advancement: Manage external CRO partnerships and biotech collaborations, providing scientific expertise to support discovery campaigns including DNA-encoded library (DEL), phage display, and yeast display. Foster strategic research collaborations and stay at the forefront of study design, model development, and New Approach Methodologies (NAMs) to maintain a competitive edge in animal health research.
What You Need to Succeed (minimum qualifications):
  • Education: Ph.D. in Cell/Molecular Biology, Pharmacology, Biochemistry, or a related field with several years of postdoctoral training.
  • Experience: Professional experience in industry research and early-stage biotech/drug discovery, including CRO management and experience with integrated digital discovery and HTS platforms.
  • Top 2 skills:Expert in target identification and validation: Including biological assay development for small/large molecules and expertise in high-throughput approaches to validate and identify targets (e.g., DEL, virtual screening).Expertise in New Approach Methodologies (NAMs): Such as organoids/iPSCs and CRISPR/Cas9 screening, with high proficiency in using AI/ML and deep learning for target validation and phenotypic profiling.
What will give you a competitive edge (preferred qualifications):
  • 3 years of experience in a pharmaceutical company, preferably in animal health.
  • Demonstrated success identifying novel targets and a proven publication record.
  • Experience with generative AI (e.g., ProteinMPNN) for de novo protein design and affinity maturation.
  • Demonstrated ability to lead projects in a fast-paced, agile environment; ability to collaborate and influence cross-functionally
  • Working knowledge of applicable statistical principles and data analysis techniques.
  • Experience with compound library screening and biomolecular training (RNA-seq, omics, flow cytometry).
Additional Information:
  • Travel: up to 25 %
  • Location: Global Elanco Headquarters - Indianapolis, IN - Hybrid Environment

Don’t meet every single requirement?Studies have shown underrepresented groups are less likely to apply to jobs unless they meet every single qualification. At Elanco we are dedicated to building a diverse and inclusive work environment. If you think you might be a good fit for a role but don't necessarily meet every requirement, we encourage you to apply. You may be the right candidate for this role or other roles!

Elanco Benefits and Perks:

We offer a comprehensive benefits package focusing on financial, physical, and mental well-being while encouraging our employees to pursue our purpose! Some highlights include:

  • Multiple relocation packages
  • Two weeklong shutdowns (mid-summer and year-end) in the US (in addition to PTO)
  • 8-week parental leave
  • 9 Employee Resource Groups
  • Annual bonus offering
  • Flexible work arrangements
  • Up to 6% 401K matching

Elanco is an EEO/Affirmative Action Employer and does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

Elanco may use automated tools, including AI, to support parts of our recruitment process, such as reviewing applications against job-related criteria and/or transferrable skills. These tools help ensure a consistent, structured evaluation, but they do not make hiring decisions. All decisions involve a human reviewer. For more information on how we handle personal data, please see our Elanco Workforce Privacy Notice.

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