Materials Informatics Scientist

Jobtailor

Plymouth (MO)

On-site

USD 140,000 - 190,000

Full time

6 days ago

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Job summary

Jobtailor is seeking a highly qualified researcher to lead generative AI and physics-informed ML initiatives across product and materials development. You will develop data-driven models to accelerate discovery of new materials and processes for sustainable mobility solutions, collaborating with global teams and presenting findings to executive audiences.

Ideal candidates hold a PhD with 3+ years in computational materials science, with strong programming skills in Python/Julia/C/C++, and

Qualifications

PhD or equivalent in materials science, chemistry, chemical engineering, data science, CS, physics, or related field.
3+ years of experience in computational methods for material and product design.
Strong knowledge of structure–property relationships and materials characterization.
Experience with cheminformatics, materials informatics, Generative AI, ML tools for simulations.
Proficiency in Python, Julia, C/C++, plus SQL/MySQL/MongoDB/Flask/Azure or other cloud tech.
Ability to work independently and in a team.
Strong communication and stakeholder engagement.
Willingness to travel is a plus.
Excellent analytical, problem solving, and critical thinking.
Ability to manage multiple projects in a fast-paced, globally matrixed environment.

Responsibilities

Lead activities in generative AI and physics-informed ML for product, formulation, material/process discovery and design.
Develop advanced data-driven and physics-based models to guide development of products, materials, and processes.
Analyze and interpret materials data using advanced statistics and data mining techniques.
Propose, execute and defend project concepts.
Collaborate and plan experimental campaigns for model development, validation and deployment with Freudenberg Business Groups.
Identify and prioritize promising materials candidates for further investigation.
Work with internal and external experts to develop high business impact solutions.
Communicate results through reports and presentations to technical and non-technical audiences, including C level.
Collaborate with materials scientists, engineers, and researchers across geographic locations.
Collaborate with industry or academic specialists to apply results and develop new techniques.

Skills

Generative AI

Physics-informed ML

Python

C/C++

Julia

Mathematical modeling

Data mining

Statistical analysis

Experiment planning

Project management

Communication

Education

PhD in Materials Science

Tools

Python

Julia

C/C++

SQL

MySQL

MongoDB

Flask

Azure

Cloud Technologies

Machine Learning Tools

Job description

Lead activities in generative AI and physics-informed machine learning for product, formulation, material/process discovery and design
Develop advanced data-driven and physics-based models to guide and accelerate the development of products, materials and processes for sustainable solutions and new mobility applications
Analyze and interpret materials data using advanced statistical and data mining techniques
Propose, execute and defend project concepts
Collaborate and plan experimental campaigns for model development, validation and deployment with Freudenberg Business Groups
Identify and prioritize promising materials candidates for further investigation and development
Work with internal and external experts to develop high business impact solutions
Communicate results through reports and presentations to technical and non-technical audiences, including C level
Collaborate with materials scientists, engineers, and researchers across geographic locations
Collaborate with industry or academic specialists to apply research results and develop new techniques

Requirements

PhD or equivalent experience in materials science, chemistry, chemical engineering, data science, computer science, physics, mechanical engineering, or a related field
Minimum 3+ years of experience in computational methods for material and product design, either in industry or academia
Strong knowledge of materials science fundamentals, including structure-property relationships, materials characterization, and the principles governing material properties and behavior
Experience with cheminformatics, materials informatics, Generative AI, ML tools for accelerating multiscale and multiphysics simulations
Proficiency in programming languages like Python, Julia, C/C++, and familiarity with SQL, MySQL, MongoDB, Flask, Azure, or other cloud technologies
Ability to work independently and as part of a team
Strong communication and stakeholder engagement skills
International outlook and willingness to travel as a plus
Excellent analytical, problem/situation analysis, and critical thinking skills
Ability to manage multiple projects and meet deadlines in a fast-paced, globally matrixed environment

Core Competencies

Demonstrates expertise in generative AI and physics-informed machine learning for product and material development, with strong analytical skills in data interpretation and modeling. Proficient in collaborating with cross-functional teams and communicating complex results to diverse audiences.

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