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Internship Machine Learning Chemistry Jobs in Michigan

Solid Knowledge of battery chemistry and battery manufacturing. * Excellent experience in modeling of electrochemical systems. * Solid knowledge of machine learning, data cleaning, cloud computing ...

Solid Knowledge of battery chemistry and battery manufacturing. * Excellent experience in modeling of electrochemical systems. * Solid knowledge of machine learning, data cleaning, cloud computing ...

... chemistry experience gained through academic work, internships, or industry roles. * Comfort and ... Interest in ongoing learning and collaboration with research universities and organizations. Work ...

Build team and expertise with cross functional expertise in cell chemistry, data analytics, BMS ... Applying Data Analytics and Machine Learning; Utilizing Databricks, INCA, CDA, CAN, CANalyzer, and ...

Bachelor's degree or higher in Biology, Microbiology, Chemistry, or a related field. * Extensive ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Bachelor's degree or higher in Biology, Microbiology, Chemistry, or a related field. * Extensive ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Bachelor's degree or higher in Biology, Microbiology, Chemistry, or a related field. * Extensive ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Showing results 41-60

Internship Machine Learning Chemistry information

What are some common challenges faced during a machine learning chemistry internship, and how can interns overcome them?

Interns in Machine Learning Chemistry often encounter challenges such as bridging the gap between computational methods and chemical domain knowledge, working with complex and sometimes limited datasets, and adapting to rapidly evolving technologies. To overcome these hurdles, it's helpful to proactively seek mentorship from both data scientists and chemists within the team, dedicate time to learning domain-specific concepts, and regularly participate in team discussions to clarify project goals. Embracing a collaborative mindset and staying curious will also help interns effectively contribute and grow in this interdisciplinary environment.

What are the key skills and qualifications needed to thrive as an internship in machine learning chemistry?

To thrive as an intern in Machine Learning Chemistry, you need a solid understanding of chemistry fundamentals and proficiency in programming languages such as Python, often supported by ongoing or completed coursework in chemistry, computer science, or related fields. Familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow), cheminformatics tools (e.g., RDKit), and data analysis platforms is highly valued. Strong analytical thinking, problem-solving skills, and teamwork set standout candidates apart in collaborative research environments. These skills are important to effectively develop, implement, and interpret machine learning models that address complex chemical problems.

What is an internship in machine learning chemistry?

An Internship in Machine Learning Chemistry is a temporary, often academic or industry-based position where students or early-career professionals gain hands-on experience applying machine learning techniques to solve problems in chemistry. Interns may work on projects involving data analysis, molecular modeling, drug discovery, or material design using algorithms and computational tools. The internship provides practical exposure to interdisciplinary research, allowing interns to collaborate with chemists, data scientists, and engineers. It is an excellent opportunity to develop both technical and professional skills in a rapidly growing field.

What is the difference between Internship Machine Learning Chemistry vs Chemistry Research Intern?

AspectInternship Machine Learning ChemistryChemistry Research Intern
Required CredentialsBasic programming, chemistry knowledge, courseworkChemistry coursework, lab skills, basic research experience
Work EnvironmentData analysis, coding, computational toolsLaboratory experiments, chemical analysis
Industry UsageTech companies, research labs integrating ML and chemistryAcademic, industrial chemistry labs
Search & Comparison IntentUnderstanding roles combining ML and chemistry internshipsTraditional chemistry research internship details

Internship Machine Learning Chemistry focuses on applying machine learning techniques to chemistry problems, often involving coding and data analysis. In contrast, Chemistry Research Internships emphasize hands-on laboratory research in chemistry. Both roles require chemistry knowledge, but the former integrates computational skills, making it ideal for those interested in data-driven chemistry careers.

What cities in Michigan are hiring for Internship Machine Learning Chemistry jobs?

Cities in Michigan with the most Internship Machine Learning Chemistry job openings:

Infographic showing various Internship Machine Learning Chemistry job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Battery Modeling Engineer

A123 Systems LLC

Novi, MI โ€ข Hybrid

Full-time

Re-posted 27 days ago


Job description

A123 Systems, LLC is a leading developer and manufacturer of advanced lithium-ion battery technologies and energy storage systems. Our solutions serve a wide range of applications, from traditional automotive batteries to utility-scale and commercial amp; industrial (C amp;I) energy storage. Committed to safety, longevity, and energy efficiency, A123 delivers high-performance battery technology solutions with a strong commitment to grow and serve our customers, industry requirements with the goal to make the Air Cleaner.
Position Overview
The Advanced Simulation Technology amp; AI Department at A123 Systems is hiring a Battery Modeling Engineer with the major responsibilities of developing physics-based models for different cell chemistry to understand the aging mechanisms and optimize the cell design, and developing data-driven AI machine learning models to optimize battery cell manufacturing process. Other responsibilities include conducting cell-, module-, and pack-level life simulation for Li-ion battery systems used in electric vehicles, plug-in hybrid electric vehicles, hybrid electric vehicles, energy storage systems, drone and electric vertical take-off and landing.
Primary Responsibilities
  • Develop physics-based models to identify aging mechanisms and optimize cell design.
  • Develop data-driven AI machine learning models to optimize the design of battery cell manufacturing process considering the cell quality control and capital costs.
  • Support NBO and regular life simulation activities through global collaboration.
  • Work in a global team and collaborate with cross-functional team colleagues.
  • Communicate findings to external customers in a positive and constructive manner, and establish/maintain technical communications for any open issues.
Specific Skills/Experience
  • Solid knowledge of electrochemical modeling and battery aging.
  • Solid Knowledge of battery chemistry and battery manufacturing.
  • Excellent experience in modeling of electrochemical systems.
  • Solid knowledge of machine learning, data cleaning, cloud computing, etc.
  • Sophisticated software/programming skills, such as COMSOL, Matlab, Python, etc.
  • Experience with ML libraries, i.e., Tensor Flow, PyTorch, etc.
  • Experience in Li-ion battery modeling and machine learning in industry is a plus.
  • Strongly self-motivated and willingness to learn new knowledge.
  • 0-2 years industry working experience.
Education
  • Ph.D. degree in Engineering, Physics, Math, Statistics, Analytics, etc.