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Machine Learning Material Science Postdoc Jobs (NOW HIRING)

MS or PhD degree from an accredited university in Engineering, Data Science, Computer Science, Machine Learning, Materials Science, Mathematics, Statistics, or Analytics. * Minimum of 2 years of ...

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Machine Learning Material Science Postdoc information

What is a machine learning material science postdoc?

A Machine Learning Material Science Postdoc is a researcher who applies advanced machine learning techniques to solve problems in material science. This role typically involves developing algorithms to predict material properties, optimize materials design, and analyze complex datasets generated from experiments or simulations. Postdocs in this field often work in interdisciplinary teams, collaborating with chemists, physicists, and engineers. Their research can accelerate the discovery of new materials for applications such as energy storage, electronics, and manufacturing.

What are the key skills and qualifications needed to thrive as a machine learning material science postdoc?

To thrive as a Machine Learning Material Science Postdoc, you need a doctoral degree in materials science, physics, chemistry, or a related field, along with a strong foundation in machine learning algorithms and data analysis. Familiarity with programming languages such as Python, machine learning libraries (e.g., TensorFlow, PyTorch), and materials simulation software is essential. Strong problem-solving abilities, collaboration skills, and effective scientific communication help you work across interdisciplinary teams and present research findings. These skills ensure innovative research, accurate modeling, and impactful contributions to the advancement of material science using AI.

How does a machine learning material science postdoc typically collaborate with experimental researchers in multidisciplinary teams?

As a Machine Learning Material Science Postdoc, you will frequently work alongside experimental scientists, chemists, and engineers. Collaboration often involves translating experimental data into machine learning models, suggesting new experiments based on predictive insights, and validating computational results with laboratory outcomes. Clear communication and interdisciplinary understanding are key, as you bridge the gap between computational modeling and practical material synthesis or characterization. This collaborative environment not only enhances research outcomes but also broadens your professional skill set.

What are popular job titles related to Machine Learning Material Science Postdoc jobs?

For Machine Learning Material Science Postdoc jobs, the most frequently searched job titles are:

Infographic showing various Machine Learning Material Science Postdoc job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer

Whitehall, MI • On-site

Howmet Aerospace Inc.
Aviation • 10K+ employees

Other

Posted 4 days ago


Howmet Aerospace rating

7.8

Company rating: 7.8 out of 10

Based on 166 frontline employees who took The Breakroom Quiz


Job description

  • Locations One Misco Drive, Whitehall, MI, 49461-1799, US (On-site)
  • Job Schedule Full time
  • Export-Controlled Data This position entails access to export-controlled items and employment offers are conditioned upon an applicant's ability to lawfully obtain access to such items
Responsibilities

Howmet Aerospace is hiring a Machine Learning Engineer with expertise in deep learning to join our innovative Research and Development team. This role involves building cutting-edge machine learning and deep learning applications and collaborating with cross-functional teams to support our casting, alloy, core, and rings facilities.

The position is located in Whitehall, Michigan in our Howmet Research Center (HRC).

Primary Responsibilities

  • Design, develop, and evaluate advanced deep learning architectures (e.g., CNNs, Mask R-CNNs, YOLO) to address complex manufacturing challenges.
  • Train and optimize generative models to accelerate development (e.g., diffusion models, VAEs, GANs).
  • Build and refine machine learning algorithms to enhance Howmet products across all business units.
  • Construct, manipulate, and analyze large datasets using tools such as Python and SQL.
  • Leverage transfer learning techniques and pretrained models to achieve strong performance with limited data.
  • Fine‑tune existing models for specific applications and datasets.
  • Develop customized deep learning architectures to handle diverse data types.
  • Conduct statistical multi-factor analyses to uncover complex relationships and improve manufacturing processes.
  • Present data-derived conclusions to a non-technical audience.
  • Identify opportunities to optimize processes and implement continuous improvement tools using machine learning.
  • Promote a data-driven culture across the organization by expanding machine learning applications and leading training initiatives.
  • Collaborate with internal customers to validate trials, implement process enhancements, and integrate machine learning into production workflows.
Qualifications

Basic Qualifications:
MS or PhD degree from an accredited university in Engineering, Data Science, Computer Science, Machine Learning, Materials Science, Mathematics, Statistics, or Analytics.
Minimum of 2 years of hands-on experience in deep learning and machine learning demonstrating ability to apply advanced statistical methods and machine learning algorithms to production/field data using Python.
Experience with feature engineering techniques (feature creation, selection, and transformation).
Employees must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is not available for this position.
This export- control language can be added directly to the job posting in the Job Info box of the posting by selecting the sentence in the dropdown field titled "Export-Controlled Data" in section 4 of the job requisition

Preferred Qualifications:
Minimum of 5 years of professional experience in data science or machine learning.
Theoretical understanding and practical experience applying reinforcement learning techniques for real time decision making and control.
Experience using generative models such as diffusion models, VAEs and GANs
Comprehensive knowledge of advanced analytics and machine learning techniques.
Strong statistical background with demonstrated expertise in analyzing industrial/manufacturing data.
Familiarity with manufacturing or industrial plant environments and their unique challenges.
Knowledge of software development life cycle (SDLC)
Proficiency in visualization tools (e.g., Power BI)
Exceptional verbal and written communication skills with the ability to convey complex ideas clearly.
Strong organizational skills and the ability to work independently and in a cross-functional team environment.

Why Join Us?
Be at the forefront of innovation, applying machine learning to aerospace manufacturing.
Collaborate with a supportive, cutting-edge team dedicated to solving challenging real-world problems.
Access professional growth opportunities and a chance to directly impact Howmet Aerospace’s success.

About Us

Howmet Aerospace Inc. (NYSE: HWM), headquartered in Pittsburgh, Pennsylvania, is a leading global provider of advanced engineered solutions for the aerospace and transportation industries. Our primary businesses focus on jet engine components, aerospace fastening systems, titanium structural parts and forged wheels. With $8.3 Billion in revenue in 2025, our products play a crucial role in enabling fuel efficiency and lightweighting, contributing to our customers’ success and making a positive impact on the world. To learn more about the way Howmet Aerospace Inc. is advancing the sustainability of our customers, markets, and communities where we operate, review the 2025 Environmental Social and Governance report at www.howmet.com/esg-report . Follow: LinkedIn , Twitter , Instagram , Facebook , and YouTube .

Equal Opportunity Employer:

Howmet is proud to be an Equal Employment Opportunity employer. We are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or other applicable legally protected characteristics.

The Howmet engines business produces world-class aerospace engine components, including investment castings, fasteners, rings and forgings. Our vacuum melted superalloys, machining, performance coatings and hot isostatic pressing for high performance parts enable the next generation of quieter, cleaner and more fuel-efficient aerospace engines. Able to supply more than 90% of structural and rotating aerospace engine components.

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About Howmet Aerospace

Sourced by ZipRecruiter

Howmet Aerospace Inc. (NYSE: HWM), headquartered in Pittsburgh, Pennsylvania, is a leading global provider of advanced engineered solutions for the aerospace and transportation industries. The Company's sales for 2021 approximated $5 billion. The Company's primary businesses focus on jet engine components, aerospace fastening systems, titanium structural parts and forged wheels. With nearly 1,150 granted and pending patents, the Company's differentiated technologies promote more fuel efficiency for aircraft and commercial transportation. Howmet is proud to be an Equal Employment Opportunity and Affirmative Action employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Industry

Aviation

Company size

10,000+ Employees

Headquarters location

Pittsburgh, PA, US

Year founded

1888