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Machine Learning Computational Chemistry Jobs in Maryland

Varsity Tutors

Physical Chemistry Tutor

Baltimore, MD · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Adapts instruction using computational chemistry software, worked derivations, and visual quantum ...

Varsity Tutors

Physical Chemistry Tutor

College Park, MD · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Adapts instruction using computational chemistry software, worked derivations, and visual quantum ...

Varsity Tutors

Physical Chemistry Tutor

Laurel, MD · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Adapts instruction using computational chemistry software, worked derivations, and visual quantum ...

Varsity Tutors

Physical Chemistry Tutor

Rockville, MD · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Adapts instruction using computational chemistry software, worked derivations, and visual quantum ...

Varsity Tutors

Physical Chemistry Tutor

Bowie, MD · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Adapts instruction using computational chemistry software, worked derivations, and visual quantum ...

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All JobsMachine Learning Computational Chemistry JobsMachine Learning Computational Chemistry Jobs in Maryland

Machine Learning Computational Chemistry information

See Maryland salary details

$24.4K

$114.1K

$210.8K

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

As of Aug 25, 2026, the average yearly pay for machine learning computational chemistry in Maryland is $114,097.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,749.00 and $153,997.00 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.

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

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

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

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

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

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

Machine Learning Computational Chemistry jobs near you

Computational Soft Matter Modeler

Johns Hopkins Applied Physics Laboratory

Laurel, MD • On-site

$290K/yr

Full-time

Posted 5 days ago

Johns Hopkins Applied Physics Laboratory rating

9.6

Company rating: 9.6 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

2nd of 74 rated research

Job description

Description
Are you a creative person driven to solve new problems?
Are you searching for impactful work in computational engineering and research that doesn't confine you to working on the same thing year after year?
Does making meaningful contributions to projects using synthetic and bio-derived polymers to solve problems in human health, sensing, and biomanufacturing sound like a dream job?
If so, we're looking for someone like you to join our team at APL.
We are seeking a Computational Soft Matter Modeler to help model key physical processes in complex systems involving soft materials, including polymers and biopolymers, to solve impactful challenges. As a member of our team, you will contribute to exciting projects supporting the US Department of Defense and other government agencies. Our team strives to develop, apply, and maintain deep expertise in multiscale modeling techniques that give insight across key length and time scales. You will work alongside analysts, laboratory scientists, and engineers who have a passion for applying our modeling results to physical systems that advance the state of the art and have real-world impact.
As a Computational Soft Matter Researcher, you will:
  • Develop and use models of macromolecules to determine relationships between structure and function across a variety of length and time scales, from enzymatic activity and chemical reactivity, to large-scale mechanical properties and flow.
  • Perform and develop analyses spanning a broad range of macromolecular characteristics including structural, thermodynamic, chemical, and electromagnetic phenomena.
  • Leverage modeling methods including classical molecular dynamics, computational chemistry, coarse graining, enhanced sampling, statistics, and machine learning.
  • Actively collaborate with analysts, scientists, and engineers on a day-to-day basis.
  • Propose future projects and initiatives.
  • Craft reports and give presentations to communicate results to team members and government partners.

We're looking for talented and versatile computational researchers who are excited to expand their analytical toolbox. If you have experience in any of the methods or tools above, and are motivated to learn even more, we want to talk to you.
Qualifications
You meet our minimum qualifications for the job if you have:
  • A Ph.D. in Biochemical, Chemical or Mechanical Engineering, Biology, Chemistry, Physics, Applied Mathematics, or equivalent with demonstrated application of knowledge to answer complex questions.
  • 3+ years of experience in performing physics-based simulations of macromolecules, such as quantum-chemistry calculations, classical molecular dynamics or coarse-grained molecular models.
  • Demonstrated ability to work both independently with minimal guidance, and collaboratively within a multidisciplinary team environment.
  • Demonstrated ability to communicate and collaborate with experimental colleagues.
  • Ability to manage and prioritize multiple projects.
  • Excellent verbal and written communication skills.
  • Willingness and ability to travel occasionally to attend meetings or tests at other government and contractor sites.
  • Ability to work in closed area facilities.
  • Are able to obtain a Secret level security clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

You'll go above and beyond our minimum requirements if you have:
  • Experience developing models of macromolecules that convey information across simulations at different length/time scales or physics.
  • Experience modeling macromolecules and their environmental interactions for specific applications in sensing, biomanufacturing, or medical countermeasures.
  • Expertise in developing and/or applying machine learning models for accelerated simulation, screening, or design of macromolecules.
  • Scientific/engineering programming experience, with the ability to work in multiple languages (MATLAB, C/C++, Python, FORTRAN, ...) and algorithms commonly used in computational science and engineering.
  • Experience using hardware accelerators (e.g. GPUs) and familiarity with parallel programming techniques (MPI/OpenMP).
  • Demonstrated ability to contribute to team-based software development.
  • A track record of concurrently contributing impactful technical work to multiple efforts.
  • Experience collaborating closely with experimental colleagues to develop novel approaches or technical solutions.

Minimum Rate
$105,000 Annually
Maximum Rate
$290,000 Annually

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