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Machine Learning Chemistry Jobs in Pennsylvania (NOW HIRING)

PPG

Senior Data Scientist

Pittsburgh, PA · On-site +1

... Engineering, Chemistry, Physics, or related field. * 5+ years of experience delivering AI/ML solutions in production environments * Strong expertise in: * Machine learning and deep learning

MSD

Senior Specialist, Data Science

West Point, PA · On-site

$129K - $203K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... Chemistry, Data Engineering, Data Modeling, Data Science, Data Visualization, Environmental Toxicology, Foundation Engineering, Large Language Models (LLMs), Machine Learning (ML), Machine Learning ...

Jj

Technical Product Manager, Chemistry IT Systems

Spring House, PA

$159K - $184K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Understand the global deployment of AI and machine learning capabilities for molecular invention, including AI-enabled search experiences that allow chemists to retrieve information using natural ...

Merck & Co.

$129K - $203K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... Chemistry, Data Engineering, Data Modeling, Data Science, Data Visualization, Environmental Toxicology, Foundation Engineering, Large Language Models (LLMs), Machine Learning (ML), Machine Learning ...

The Pennsylvania State University

  • Medical

Quantum Machine Learning and AI: Develop novel quantum algorithms and computational frameworks for ... chemistry, biology, healthcare, and other data-intensive scientific domains. This position aligns ...

IQVIA

AI Solutions Delivery 3 (Remote)

Wayne, PA · Remote

Our team offerings leverage advanced analytics, machine learning algorithms, and technology ... Qualifications BA/BSc preferably related to life sciences, chemistry, economics, business ...

IQVIA

AI Solutions Delivery 3 (Remote)

Wayne, PA · Remote

Our team offerings leverage advanced analytics, machine learning algorithms, and technology ... Qualifications BA/BSc preferably related to life sciences, chemistry, economics, business ...

The Pennsylvania State University

The position will involve machine learning for autonomous thin-film materials synthesis, including ... Domain knowledge of materials science, chemistry, or physics will be an advantage. Extensive ...

CMR University

Professor & HOD, Artificial Intelligence & Machine Learning (AI & ML) * HOD, ECE * Assistant ... Basic Sciences (Physics/Chemistry/Mathematics) For details please click on Qualifications and ...

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Machine Learning Chemistry information

What are the key skills and qualifications needed to thrive in machine learning chemistry?

To thrive in a Machine Learning Chemistry role, you need a solid background in chemistry, expertise in data science and machine learning algorithms, and typically an advanced degree in chemistry, computer science, or a related field. Familiarity with programming languages like Python or R and experience working with cheminformatics tools and machine learning frameworks (such as TensorFlow or scikit-learn) are essential. Strong analytical thinking, problem-solving abilities, and effective communication skills enable professionals to bridge the gap between computational work and experimental research teams. These competencies are crucial for developing innovative solutions in chemical research and ensuring successful collaboration across interdisciplinary teams.

What is a machine learning chemistry?

A Machine Learning Chemistry job involves using artificial intelligence techniques to analyze chemical data, model molecular behaviors, and accelerate discoveries in chemistry-related fields. Professionals in this role develop and apply machine learning algorithms to predict chemical properties, optimize reactions, and assist in drug design, material science, and other applications. They typically work in pharmaceuticals, materials science, or environmental chemistry, collaborating with chemists, data scientists, and engineers to solve complex chemical problems efficiently.

What does a machine learning chemistry do?

Professionals in Machine Learning Chemistry often work on projects such as developing predictive models for chemical property analysis, optimizing molecular structures, or advancing drug discovery through data-driven methods. Daily tasks may include data preprocessing, building and training machine learning models, validating results, and interpreting outcomes in collaboration with experimental chemists. Teamwork is common, with regular interactions between chemistry researchers, data scientists, and software engineers. This structure allows for iterative feedback and ensures that computational models align with practical lab needs. Continuous learning and adaptation are also key, as both the chemistry and machine learning fields are rapidly evolving.

What are the most commonly searched types of Machine Learning Chemistry jobs in Pennsylvania?

The most popular types of Machine Learning Chemistry jobs in Pennsylvania are:

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

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

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

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

Machine Learning Chemistry jobs near you
Infographic showing various Machine Learning Chemistry job openings in Pennsylvania as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 26% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Postdoctoral Research Associate - Isayev Lab

Carnegie Mellon University

Pittsburgh, PA • On-site

Full-time

Re-posted 18 days ago

Carnegie Mellon University rating

8.6

Company rating: 8.6 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

67th of 618 rated colleges and universities

Job description

Description
The Isayev Lab at Carnegie Mellon University invites applications for a postdoctoral researcher to lead projects at the interface of computational chemistry, machine learning, reaction mechanism elucidation, and automated molecular discovery. The position is ideal for a candidate who wants to turn deep mechanistic understanding into predictive models and closed-loop discovery workflows.
Our lab develops and applies machine learning methods for computational chemistry, materials science, and molecular discovery, including transferable neural network potentials, generative molecular design, and experiment-automation workflows. The postdoc will work in a collaborative CMU environment spanning computational chemistry, AI, automated experimentation, polymer chemistry, and catalysis.
Research directions may include:
Developing automated DFT / ML workflows for mechanistic studies of photoredox, organometallic, and radical catalytic reactions.
Building predictive models that connect quantum-chemical descriptors, catalyst structure, substrate scope, selectivity, and reaction performance.
Applying AIMNet2 and related ML/QM methods to accelerate conformer search, reaction-path exploration, catalyst screening, and high-throughput mechanistic modeling.
Designing closed-loop computational-experimental campaigns for transition metal catalysis, polymer synthesis, and related catalytic transformations.
Creating reusable, open, well-documented software workflows for reaction data generation, curation, featurization, and model deployment.
Collaborating with experimental groups at CMU and external partners to convert mechanistic hypotheses into experimentally testable predictions.
Qualifications
Desired background:
Ph.D. in chemistry, chemical engineering, materials science, or a related field.
Strong experience in computational reaction mechanisms, especially DFT studies of organic, organometallic, photoredox, radical, or homogeneous catalytic systems.
Fluency with Python and modern scientific computing workflows; experience with Git, HPC clusters, SLURM, Gaussian, ORCA, Q-Chem, xTB, RDKit, ASE, or related tools is highly valued.
Interest in machine learning, statistical modeling, active learning, descriptor development, or data-driven reaction prediction.
Ability to work closely with experimental collaborators and communicate mechanistic insight clearly.
Application Instructions
Applications, including a cover letter and a curriculum vitae indicating your interest and relevant training should be submitted electronically via Interfolio.

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