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Associate Machine Learning Chemistry Jobs in California

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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 California?

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

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

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

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

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

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

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

Associate Machine Learning Chemistry jobs near you

Machine Learning Engineer

South San Francisco, CA • On-site

Tranzeal Incorporated
Business Management Consulting • 51 - 200 employees
Learn more about Tranzeal Incorporatedexternal

Full-time

Re-posted 17 days ago

Job description

Job Summary:
Tranzeal Incorporated is seeking talented Machine Learning Engineers to join Prescient Design, a division focused on molecular design methods. The successful candidate will manage projects deploying machine learning techniques for drug design and optimization.
Responsibilities:
• You will join Prescient Design within the Computational Sciences organization in gRED.
• Your peers will be machine learning scientists, engineers, computational chemists, and computational biologists.
• You will closely collaborate with scientists within Prescient and across gRED.
• You will develop machine learning and Bayesian optimization workflows to analyze existing, and design new, small and large molecules.
• You will be expected to form close working relationships with small molecule and protein therapeutic development efforts across the gRED organization.
• You will be expected to work on existing projects and generate new project ideas.
Qualifications:
Required:
• PhD degree in a quantitative field (e.g., Computer Science, Chemistry, Chemical Engineering, Computational Biology, Physics), or MS degree and 3+ years of industry experience.
• Demonstrated experience with machine learning libraries in production-ready workflows (e.g., PyTorch + Lightning + Weights and Biases)
• Record of achievement, including at least one high-impact first author publication or equivalent.
• Excellent written, visual, and oral communication and collaboration skills.
Preferred:
• Experience with physical modeling methods (e.g., molecular dynamics) and cheminformatics toolkits (e.g., rdkit)
• Previous focus on one or more of these areas: molecular property prediction, computational chemistry, de novo drug design, medicinal chemistry, small molecule design, self-supervised learning, geometric deep learning, Bayesian optimization, probabilistic modeling, statistical methods.
• Public portfolio of computational projects (available on e.g. GitHub)
Company:
Tranzeal is an industry leading global Business Transformation Service Provider. Founded in , the company is headquartered in San Jose, USA, with a team of 201-500 employees. The company is currently Growth Stage.
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About Tranzeal

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Tranzeal is an industry leading global Business Transformation Service Provider. We offer specific consulting services as well as pre-packaged, industry specific solutions and services to companies around the world. Since our foundation, Tranzeal has evolved from a small start up company to a mid market player dedicated to providing solutions and services to SMB and large enterprise customers. Our Consulting Services are dedicated to helping our Clients maximize their investments in IT and the overall effectiveness and efficiency of the business. Tranzeal has built its center of competency in Enterprise Resource Planning, Business Intelligence, Supply Chain Management, Customer Resource Management and Information Integration solutions, as well as specific Service orientated offerings such as Test, Quality Assurance and Data Management.

Industry

Business management consulting

Company size

51 - 200 Employees

Headquarters location

San Jose, CA, US

Social media

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