Research Scientist

The 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.

Electrical Engineering has been primarily responsible for the information technology revolution that society is experiencing. The development of large-scale integrated circuits has led to the development of computers and networks of ever-increasing capabilities. Computers greatly influence the methods used by engineers for designing and problem solving.

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).