Associate Director, Engineering Sciences - BioMechanics

Secretariat•Chicago, IL

About The Position

As part of our expanding Global Engineering and Scientific consulting team, you will work at the forefront of today’s most complex engineering challenges. You will be engaged in analyzing failures of a myriad of products from a variety of industries, but with a heavy focus on large industrial facilities like power plants, Oil & Gas facilities, chemical processing plants, construction, and similar. Outside of that work, you will be engaged in automotive, consumer products, consumer electronics, and medical devices. Secretariat leverages our diverse technical expertise and industry knowledge of a variety of structures and products to provide clients with world-class value to identify solutions that drive performance and safety. Secretariat is a diversified international expert services firm with more than 500 professionals in 20+ cities around the globe. Furthermore, Secretariat was recently ranked as the #1 firm in Global Arbitration Review’s prestigious GAR 100 Expert Witness Firms’ Power Index, and more than 90% of Secretariat’s leading experts are recognized as leading experts in their field by the independent Lexology rankings.

Requirements

Ph.D. in Biomechanics, Biomedical Engineering, Mechanical Engineering, Kinesiology, Bioengineering, Data Science, Electrical Engineering, or a related technical discipline.
Strong background in biomechanics, human movement analysis, signal processing, and advanced data analytics.
Experience working with wearable biomechanical, physiological, and integrated clinical sensing technologies.
Experience developing analytical pipelines, algorithms, or software tools for integrated wearable and laboratory-based sensor data processing and analysis.
Strong understanding of multimodal wearable sensing technologies and associated signal characteristics.
Experience conducting or supporting human-subject/participant studies.
Experience processing and analyzing large-scale time-series datasets generated from diverese sensing systems.
Experience applying statistical analysis, machine learning, or AI methodologies to biomechanics, physiological monitoring, or other human movement datasets.
Strong programming and scientific computing skills using Python, MATLAB, R, and/or C/C++.
Strong written and verbal communication skills.

Responsibilities

Design and develop analytical pipelines for acquisition, synchronization, fusion, processing, and analysis of multimodal wearable and biomechanical sensor data.
Collect, process, analyze, and interpret biomechanical and physiological data from both laboratory and real-world study environments as they pertain to human gait and locomotion, motor control, and predictive musculoskeletal and human movement modeling.
Develop algorithms, software tools, and analytical workflows for wearable sensor and biomechanics applications.
Work extensively with wearable sensing modalities including: inertial measurement units (IMUs), photoplethysmography (PPG), galvanic skin response (GSR/EDA), electromyography (EMG), wearable force and pressure sensing systems, flexible and emerging wearable sensor technologies.
Apply signal processing, sensor fusion, statistical modeling, and AI/ML methodologies to derive meaningful insights from complex multimodal datasets.
Develop and apply machine learning and AI approaches including: predictive analytics, classification and pattern recognition, anomaly detection, time-series analytics, human activity recognition, computer vision and movement tracking.
Support development and validation of wearable sensing technologies and associated algorithms against laboratory-based gold-standard systems.
Develop technical reports, visualizations, dashboards, and presentations to communicate analytical findings and study outcomes.
Collaborate closely with multidisciplinary teams including engineers, data scientists, clinicians, researchers, and product development teams.
Contribute to technical publications and client-facing technical activities as appropriate.