Job DescriptionThe Research Engineer will develop and integrate intelligent additive manufacturing systems that combine in-situ sensing, data acquisition, computer vision, and digital twin technologies. This role focuses on building experimental and computational tools for real-time process monitoring, data fusion, and predictive modeling of material behavior.
The position is hands-on and applied, involving system integration, algorithm development, and experimental validation in collaboration with multidisciplinary engineering teams.
Duties and Responsibilities- Design, develop, and optimize additive manufacturing systems (laser powder bed fusion, directed energy deposition, or extrusion-based platforms).
- Develop and integrate in-situ sensing and monitoring systems using multi-modal sensors (thermal, optical, acoustic, and process signals).
- Build and deploy data acquisition and real-time data pipelines for manufacturing process monitoring.
- Implement data fusion and signal processing algorithms to integrate heterogeneous sensor data streams.
- Develop and maintain digital twin frameworks for simulation, prediction, and real-time process feedback.
- Apply computer vision and image processing techniques (e.g., melt pool monitoring, layer inspection, defect detection).
- Develop models linking process parameters, sensor data, and material properties (strength, fatigue, microstructure).
- Support mechanical testing and materials characterization to validate models and system performance.
- Collaborate closely with teams in mechanical engineering, materials science, data science, and systems engineering.
- Contribute to technical documentation, system reports, and internal/external presentations for stakeholders and collaborators.
Supervisory Relationships: This position has no supervisory responsibilities; this position will report directly to Professor Shekhar Bhansali.
Qualifications- A Ph.D. or a Master's Degree in Electrical Engineering, Mechanical Engineering, Materials Science, Manufacturing Engineering, Computer Engineering, or related field (Ph.D. preferred for advanced responsibilities).
- Strong experience with additive manufacturing systems and process fundamentals.
- Hands-on experience with sensing systems, instrumentation, and data acquisition hardware/software.
- Proficiency in Python and/or MATLAB for data analysis and algorithm development.
- Experience with machine learning, signal processing, or data fusion techniques applied to real-world systems.
- Strong background in image processing and computer vision (e.g., OpenCV or equivalent toolkits).
- Familiarity with modeling, simulation, or digital twin development frameworks.
- Understanding of materials behavior and structure-property relationships.
- Strong problem-solving skills with ability to work in experimental and applied engineering environments.
- Excellent communication skills and ability to work effectively in cross-disciplinary teams.
- Experience with real-time control systems or closed-loop feedback systems.
- Knowledge of metallurgy and microstructure evolution in additively manufactured materials.
- Experience with high-performance computing (HPC) or cloud-based simulation environments.
- Experience transitioning research prototypes into deployable engineering systems or industrial applications.
- Familiarity with software engineering best practices (version control, modular design, reproducibility).
