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Associate Machine Learning Chemistry Jobs in Virginia

They are seeking multiple full-time Postdoctoral Associates to develop agentic AI systems for ... chemistry, machine learning, and agentic science. Qualifications : Required : • Ph.D. in ...

Lead Machine Learning Engineer

Mclean, VA · On-site

$103K - $136K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating ... our associates work and provide value to our customers. * Design, develop, test, deploy, and ...

Lead Machine Learning Engineer

Richmond, VA

$101K - $133K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating ... our associates work and provide value to our customers. * Design, develop, test, deploy, and ...

Lead Machine Learning Engineer

Mclean, VA

$103K - $136K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating ... our associates work and provide value to our customers. * Design, develop, test, deploy, and ...

Lead Machine Learning Engineer

Richmond, VA

$101K - $133K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating ... our associates work and provide value to our customers. * Design, develop, test, deploy, and ...

Postdoctoral Associate Apply now Back to search results Job no: 536321 Work type: Research Faculty ... chemistry, machine learning, and agentic science. This full-time appointment is available ...

... in Scientific Machine Learning (SciML). • Collaborating with members of the group as well as ... Physics, Chemistry, Biology or related fields. • PhD must be awarded no more than four years ...

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Associate Machine Learning Chemistry information

What is the difference between Associate Machine Learning Chemistry vs Associate Data Scientist?

AspectAssociate Machine Learning ChemistryAssociate Data Scientist
Required CredentialsBachelor's or Master's in Chemistry, Data Science, or related fields; familiarity with ML frameworksBachelor's or Master's in Data Science, Statistics, Computer Science; programming skills in Python/R
Work EnvironmentResearch labs, pharmaceutical or chemical companies, biotech firmsTech companies, finance, healthcare, consulting firms
Employer & Industry UsageUsed in industries applying ML to chemical data, drug discovery, materials scienceApplied across industries analyzing large datasets, predictive modeling

Associate Machine Learning Chemistry focuses on applying machine learning techniques specifically to chemical and scientific data, often within research or pharmaceutical settings. In contrast, Associate Data Scientist has a broader scope, working with various data types across multiple industries. Both roles require strong analytical skills and familiarity with ML tools, but their industry focus and data types differ.

What are Associate Machine Learning Chemists?

Associate Machine Learning Chemists are professionals who combine expertise in chemistry with skills in machine learning to analyze chemical data, develop predictive models, and accelerate scientific discovery. They often work on tasks like predicting molecular properties, optimizing chemical reactions, and supporting drug discovery efforts using computational tools. Typically, these roles require a strong foundation in chemistry, programming experience (often in Python), and familiarity with machine learning libraries. Associate positions are generally entry-level or early-career roles, providing support to senior scientists and data scientists in research and development teams.

How does an Associate Machine Learning Chemistry professional typically collaborate with research scientists and engineers?

As an Associate Machine Learning Chemistry professional, you will frequently work alongside research scientists and chemical engineers to develop predictive models and analyze experimental data. Collaboration involves translating chemical problems into machine learning tasks, sharing insights from model results, and participating in interdisciplinary meetings to refine research objectives. Effective communication and teamwork are essential, as you may be required to explain machine learning concepts to non-technical colleagues and integrate their domain expertise into your models. This collaborative environment fosters both scientific discovery and professional growth.

What are the key skills and qualifications needed to thrive as an Associate Machine Learning Chemistry, and why are they important?

To thrive as an Associate Machine Learning Chemistry professional, you need a solid background in chemistry, data analysis, and machine learning, typically supported by a relevant degree such as chemistry, computer science, or a related field. Experience with programming languages like Python, machine learning libraries (e.g., TensorFlow, scikit-learn), and cheminformatics software is highly valued. Strong problem-solving skills, attention to detail, and the ability to communicate complex concepts clearly are crucial soft skills. These competencies enable effective collaboration on interdisciplinary teams and the development of innovative solutions in computational chemistry research.
What are the most commonly searched types of Machine Learning Chemistry jobs in Virginia? The most popular types of Machine Learning Chemistry jobs in Virginia are:
What cities in Virginia are hiring for Associate Machine Learning Chemistry jobs? Cities in Virginia with the most Associate Machine Learning Chemistry job openings:

Postdoctoral Associate

Virginia Tech

Blacksburg, VA • On-site

Full-time

Re-posted 4 days ago


Virginia Tech rating

7.8

Company rating: 7.8 out of 10

Based on 65 frontline employees who took The Breakroom Quiz

225th of 614 rated colleges and universities


Job description

Job Summary:
Virginia Tech is a leading global research institution dedicated to knowledge and creativity. They are seeking multiple full-time Postdoctoral Associates to develop agentic AI systems for computational catalysis and experimental design, collaborating with interdisciplinary research groups in materials discovery.
Responsibilities:
• Contribute to building AI-native frameworks that combine physics-based modeling, machine-learning methods, knowledge-graph and ontology-based scientific data infrastructures, and agentic workflows for autonomous hypothesis generation, mechanistic exploration, and design of catalytic systems.
• Collaborate closely with interdisciplinary research groups advancing materials discovery through the convergence of computational chemistry, machine learning, and agentic science.
Qualifications:
Required:
• Ph.D. in Chemistry, Chemical Engineering, Materials Science, Physics, Computer Science, or a related field. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
• Strong expertise in multiscale/multiphysics modeling relevant to catalysis, and experience with machine learning models.
• Deep understanding of reaction kinetics, thermodynamics, and structure-reactivity relationships in catalytic systems.
• Demonstrated experience with agentic AI, including automated data curation, ML model integration, workflow orchestration, or AI-assisted experimental design.
• Proven ability to conduct independent research, collaborate across disciplines, and publish high-quality scientific work.
Company:
Virginia Tech is a public research university that offers a range of academic programs and conducts research across various fields. Founded in 1872, the company is headquartered in Blacksburg, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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Hours and flexibility

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About Virginia Tech

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Virginia Tech, guided by its motto "Ut Prosim" (That I May Serve), embraces a hands-on, interdisciplinary approach to educate scholars as leaders and problem-solvers. As a comprehensive land-grant institution, it enriches the quality of life in Virginia and worldwide, fostering an inclusive community focused on knowledge, discovery, and creativity. With over 280 majors, the university serves a diverse student body of more than 36,000 across undergraduate, graduate, and professional programs. Virginia Tech's presence extends throughout Virginia, including campuses in Northern Virginia, Roanoke, Newport News, and Richmond, along with multiple Extension offices and research centers. As a prominent global research institution, it conducts over $500 million in research annually.

Industry

Colleges, universities, and professional schools

Company size

5,001 - 10,000 Employees

Headquarters location

Blacksburg, VA, US

Year founded

1872

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