What are the responsibilities and job description for the Research Scientist – Machine Learning and Polymer Chemistry position at Intelligent Automation, a BlueHalo Company?
Job Details
Description
BlueHalo has an opportunity available for a research scientist to join our multidisciplinary team at the Air Force Research Laboratory (AFRL) and contribute to cutting-edge research at the intersection of polymer science, chemistry, and machine learning.
The Research Scientist will be an integral member of the Photonic, Electronic, and Soft Materials Division, contributing to key research initiatives within the Polymers and Specialty Materials Branch. We seek a motivated candidate with a strong foundation in chemistry, polymer science, and machine learning to join our research team. The successful candidate will leverage Bayesian optimization, large language models (LLMs), and other advanced machine learning techniques such as deep learning and reinforcement learning to optimize materials synthesis. The candidate will be responsible for developing and implementing active learning algorithms in a materials synthesis workflow to advance the development of novel materials.
Excellent oral and written communication skills are a prerequisite for employment. The successful candidate will be self-motivated and capable of working independently but also collaborate with researchers from different technical backgrounds. Applications will be reviewed until the position is filled.
Primary Responsibilities Include
Description
BlueHalo has an opportunity available for a research scientist to join our multidisciplinary team at the Air Force Research Laboratory (AFRL) and contribute to cutting-edge research at the intersection of polymer science, chemistry, and machine learning.
The Research Scientist will be an integral member of the Photonic, Electronic, and Soft Materials Division, contributing to key research initiatives within the Polymers and Specialty Materials Branch. We seek a motivated candidate with a strong foundation in chemistry, polymer science, and machine learning to join our research team. The successful candidate will leverage Bayesian optimization, large language models (LLMs), and other advanced machine learning techniques such as deep learning and reinforcement learning to optimize materials synthesis. The candidate will be responsible for developing and implementing active learning algorithms in a materials synthesis workflow to advance the development of novel materials.
Excellent oral and written communication skills are a prerequisite for employment. The successful candidate will be self-motivated and capable of working independently but also collaborate with researchers from different technical backgrounds. Applications will be reviewed until the position is filled.
Primary Responsibilities Include
- Implementing machine learning and Bayesian optimization models to guide and optimize material synthesis and predict material properties.
- Applying a deep understanding of polymer chemistry, nanomaterials, and machine learning to advance the development of innovative, resilient materials.
- This position will involve working within a government facility and requires U.S. Citizenship.
- M.S. or PhD in Chemistry, Polymer Science, Chemical Engineering, Materials Science, or a related field of study required
- Machine learning and Bayesian optimization experience
- Python programming (intermediate )
- Excellent oral and written communication skills
- Ability to learn and develop new approaches and techniques
