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Machine Learning Computational Chemistry Jobs in Indiana

Indiana University

Postdoctoral Fellow, Biology

Bloomington, IN · On-site

$45K - $61K/yr

... machine learning approaches for spatial population genetics. Our research integrates custom neural ... D. in computational biology, bioinformatics, computer science, or a related field. Demonstrated ...

Amgen

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Experiencewith product ownership related to machine learning or therapeutic development,andadvancededucation inoneofthe following:Software Engineering,Computer Science, Computational Biology * A ...

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Machine Learning Computational Chemistry information

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$23K

$107.3K

$198.3K

How much do machine learning computational chemistry jobs pay per year?

As of Aug 17, 2026, the average yearly pay for machine learning computational chemistry in Indiana is $107,307.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,182.00 and $144,833.00 per year, depending on experience, location, and employer.

What is machine learning computational chemistry?

Machine learning computational chemistry is a field that combines machine learning techniques with computational chemistry to accelerate the discovery and design of molecules and materials. By training algorithms on large datasets of chemical information, researchers can predict molecular properties, simulate chemical reactions, and optimize compounds more efficiently than traditional methods. This approach helps reduce the time and cost required for research in drug discovery, materials science, and related fields.

What are some common challenges faced by professionals working in machine learning computational chemistry roles?

One common challenge in Machine Learning Computational Chemistry roles is integrating large and often complex chemical datasets with appropriate machine learning models, which requires a solid understanding of both domains. Professionals may also encounter difficulties in ensuring that their models are both interpretable and generalizable to new data, as overfitting is a frequent issue. Additionally, collaboration with chemists and data scientists is essential, so clear communication across disciplines is key to success. Staying up to date with the latest developments in both computational chemistry and machine learning is crucial for ongoing professional growth.

What are the key skills and qualifications needed to thrive as a machine learning computational chemist, and why are they important?

To thrive as a Machine Learning Computational Chemist, you need a solid background in chemistry, mathematics, and computer science, typically supported by an advanced degree in computational chemistry, cheminformatics, or a related field. Proficiency with programming languages (such as Python), machine learning frameworks (like TensorFlow or PyTorch), and molecular modeling software is essential. Strong analytical thinking, problem-solving skills, and effective collaboration are key soft skills that help drive innovation and teamwork. These skills and qualifications are critical for developing accurate models, advancing research, and translating computational insights into real-world chemical solutions.

What is the difference between Machine Learning Computational Chemistry vs Computational Chemist?

AspectMachine Learning Computational ChemistryComputational Chemist
Required CredentialsAdvanced degrees in chemistry, computer science, or related fields; knowledge of machine learning and programmingDegree in chemistry, chemical engineering, or related fields; strong background in chemical theory and modeling
Work EnvironmentResearch labs, tech companies, academia; focus on algorithm development and data analysisLaboratories, research institutions, industry; focus on chemical modeling and simulation
Employer & Industry UsageTech firms, pharmaceutical companies, research institutions applying AI/ML techniquesPharmaceutical, chemical, and materials industries conducting chemical research and development

Machine Learning Computational Chemists specialize in applying machine learning algorithms to chemical data, enhancing predictive models and simulations. Computational Chemists focus on traditional chemical modeling and simulations using computational methods. Both roles require strong chemistry backgrounds, but Machine Learning Computational Chemists emphasize data science and AI skills, while Computational Chemists focus on chemical theory and modeling techniques.

Is computational chemistry in demand?

Computational chemistry is in high demand within industries such as pharmaceuticals, materials science, and chemical research, where it supports drug discovery and molecular modeling. Professionals with skills in machine learning, programming, and chemistry are increasingly sought after to develop advanced simulation tools and analyze complex data sets.

What are popular job titles related to Machine Learning Computational Chemistry jobs in Indiana?

For Machine Learning Computational Chemistry jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Machine Learning Computational Chemistry jobs in Indiana look for?

The top searched job categories for Machine Learning Computational Chemistry jobs in Indiana are:

What cities in Indiana are hiring for Machine Learning Computational Chemistry jobs?

Cities in Indiana with the most Machine Learning Computational Chemistry job openings:

Machine Learning Computational Chemistry jobs near you
Infographic showing various Machine Learning Computational Chemistry job openings in Indiana as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $107,307 per year, or $51.6 per hour.

Postdoctoral Research Fellow - Computational Models of Coupled Natural and Human Systems

University of Notre Dame

Notre Dame, IN • On-site

Full-time

Posted 6 days ago

University Of Notre Dame rating

7.4

Company rating: 7.4 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

337th of 618 rated colleges and universities

Job description

Description
A team of faculty members affiliated with the University of Notre Dame's Just Transformations to Sustainability Initiative is seeking a highly qualified and motivated Postdoctoral Research Fellow in Computational Models of Coupled Natural and Human Systems, with a strong interest in combining forest ecology and environmental policy. This is a full-time research-focused position with no teaching responsibilities. The initial appointment is for 12 months, with the possibility of renewal for an additional 6-12 months. The successful candidate will work collaboratively with investigators from the Keough School of Global Affairs, Department of Biological Sciences, and the JTS Initiative to conduct research on local communities' forest conservation efforts.
The ideal candidate will possess expertise in computational modeling, including but not limited to statistical analysis and mechanistic computational models. They should also have experience in the analysis of remote sensing products. The successful candidate will also be expected to carry out fieldwork related to local community forest conservation efforts in Peru.
The fellow will join a dynamic, interdisciplinary team working at the intersection of data innovation and sustainability science, aligned with the values and principles of integral ecology.
The postdoctoral fellow will assume the following key responsibilities:
  • Carry out spatial analysis of Peru forest cover change using remote sensing products
  • Use an existing computational model of forest dynamics to evaluate ecological consequences of local conservation efforts
  • Carry out field work in Peru, as a member of an interdisciplinary research team, to evaluate and improve computational models
  • Work with partners to communicate research results in order to make the conservation efforts of local communities more visible to policymakers
  • Present research findings at scientific conferences and contribute to academic journal publications

The fellows will join a cohort of postdoctoral scholars supported by the Just Transformations to Sustainability Initiative, Notre Dame's University-wide effort to build a sustainable future where people and nature flourish together. The cohort works on sustainability research that engages ecological, social, economic, and ethical dimensions together rather than in isolation.
This is a full-time, in-person position with an initial appointment of one year.
Qualifications
Required Qualifcations:
  • Ph.D. (in hand by the starting date) in Forest Ecology, Environmental Science, Environmental Studies, Conservation Biology, or a related field with a strong quantitative focus.
  • Strong computational skills, with expertise in data analysis, machine learning, modeling, and programming languages such as Python, R, MATLAB, or similar.
  • Ability to spend several weeks in Peru carrying out fieldwork with local partners.
  • Excellent communication skills, with the ability to present complex research concepts clearly to both technical and non-technical audiences.

Preferred Qualifcations:
  • Familiarity with the use of spatial analysis of remote sensing data for environmental conservation, ecosystem monitoring, and climate change research.
  • Experience working in multidisciplinary teams with researchers from diverse backgrounds.
  • Ability to communicate in Spanish is a plus as is previous field research experience in the Global South

Application Instructions
Applications will close on September 7, 2026. Review of applications and interviews will take place on a rolling basis.
To apply, interested candidates must submit a CV, cover letter, and a recent publication or dissertation chapter. Candidates should be prepared to share references upon request.
Equal Employment Opportunity Statement
The University of Notre Dame seeks to attract, develop, and retain the highest quality faculty, staff and administration. The University is an Equal Opportunity Employer, and does not discriminate on the basis of race, color, national or ethnic origin, sex, disability, veteran status, genetic information, or age in employment. Moreover, Notre Dame prohibits discrimination against veterans or disabled qualified individuals, and complies with 41 CFR 60-741.5(a) and 41 CFR 60-300.5(a). We strongly encourage applications from candidates attracted to a university with a Catholic identity.
Background Check
This appointment is contingent upon the successful completion of a background check. Applicants will be asked to identify all felony convictions and/or pending felony charges. Felony convictions do not automatically bar an individual from employment. Each case will be examined separately to determine the appropriateness of employment in the particular position. Failure to be forthcoming or dishonesty with respect to felony disclosures can result in the disqualification of a candidate. The full procedure can be viewed at https://facultyhandbook.nd.edu/?id=link-73597.

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