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Associate Machine Learning Chemistry Jobs in Washington

Capital One

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 ...

Capital One

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 ...

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All JobsAssociate Machine Learning Chemistry JobsAssociate Machine Learning Chemistry Jobs in Washington

Associate Machine Learning Chemistry information

What is an associate machine learning chemistry?

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 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 the most commonly searched types of Machine Learning Chemistry jobs in Washington?

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

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

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

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

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

What cities in Washington are hiring for Associate Machine Learning Chemistry jobs?

Cities in Washington with the most Associate Machine Learning Chemistry job openings:

Associate Machine Learning Chemistry jobs near you
Infographic showing various Associate Machine Learning Chemistry job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 18% Part Time, 2% Temporary, and 5% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution.

NIST PREP Postdoc Associate Applying Machine Learning Methodologies to Predict Spectra of PFAS

Southeastern Universities Research Association

Gaithersburg, MD • On-site

$90K - $110K/yr

Full-time

Re-posted 3 days ago

Job description

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research.
Research Title: Postdoctoral Researcher Applying Machine Learning Methodologies to Predict Spectra of PFAS Compounds
The work will entail: The Materials Measurement Laboratory of the National Institute of Standards and Technology is seeking qualified persons (U.S. Citizens preferred) to apply modern methods in artificial intelligence (AI) and machine learning (ML) to the problem of predicting infrared spectra and mass spectra for PFAS compounds. The candidate should have a strong background in AI/ML with application to chemical problems, have familiarity with infrared and mass spectra, and understand the relevant chemistry of PFAS molecules. This position will involve working with a team of chemists, physicists, mathematicians, data scientists and machine learning experts characterizing PFAS molecules used in the semiconductor industry with the goal of discovering new molecules for the semiconductor etching process.
U.S. Citizen Preferred
Key responsibilities will include but are not limited to:
  • Develop libraries of training data through mining of existing databases and simulation of infrared and mass spectra using quantum chemistry and related methodologies.
  • Create AI/ML models for high-fidelity prediction of the infrared and mass spectra and validate their use in matching experimentally measured spectra.
  • Collaborate with other computational and experimental researchers to meet project goals.
  • Disseminate results through publications, talks, poster presentations, etc.

Qualifications
  • PhD. in chemistry, physics, or a closely aligned field.
  • Demonstrated experience in conducting quantum scattering calculations.
  • Strong programming skills in languages such as Python or C/C++, experience using modern software frameworks for AI/ML, and experience in data analysis.
  • Motivated, independent researcher with good organizational, communication and leadership skills.
  • Solid track-record of scientific publication.

Privacy Act StatementAuthority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)
Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate the administrative functions of the PREP Program.
Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated. By applying to a CHIPS-funded PREP opportunity, you also acknowledge that participation in the project requires signing a Non-Disclosure Agreement (NDA) prior to beginning any work.
SURA is an Equal Opportunity Employer. We believe that no one should be discriminated against because of their differences, such as age, disability, ethnicity, gender, gender identity and expression, religion, or sexual orientation. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status, or any other basis as protected by federal, state, or local law.
PREP0004008 or PREP0003620

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