Shape the future of wearable technology! The Applied Research and Characterization team combines expertise in mechanical engineering, human factors, biomechanics, data analysis, statistics, software, and advance fabrication. We deliver data-backed insights for design decisions across Apple's entire hardware portfolio, directly influencing products launched worldwide. You'll have access to cutting-edge equipment and collaborate with multidisciplinary experts across our global sites. Few teams offer this breadth of impact combined with world-class resources.\\n\\nAs an Applied Research Engineer, you'll own studies that inform wearable product development on tight timelines. You'll balance rigor with speed, take smart risks, and iterate as designs evolve. This role demands enthusiasm for working directly with diverse study participants, collaborating with cross-functional partners, strong communication skills, and the ability to excel in ambiguity. We champion continuous learning and bold experimentation. Your insights will influence products used by millions. Ready to make that impact?
The Applied Research Engineer conducts human-centered studies that drive wearable product design, often pioneering new methods for emerging categories. You'll work hands-on with prototypes, participants, and cross-functional teams to generate biomechanical, product interaction, and user experience data. You'll master new techniques and expand your capabilities while contributing to inclusive, accessible product experiences.
BS in Biomechanics, Mechanical Engineering, Biomedical Engineering, Human Factors, Anthropology, or similar disciplines \n5+ years applied research or product development experience or equivalent practical experience in R&D industry \nExperience conducting studies involving human qualitative (e.g. subjective feedback, surveys) and quantitative (e.g. interface force, pressure) data\nFull-time, on-site presence required to work with research equipment, prototypes, and study participants
Advanced degree in related field with demonstrated applied experience\nAdaptable learner who iterates quickly, takes risks, learns from failures, and is open to mentoring others\nResearch strategy, protocol design, and experimental methods (motion analysis, force measurement, physiological sensors)\nProgramming (Python, Matlab, R), statistical analysis (JMP, R, SPSS), and data visualization expertise\nApplied biomechanics, sensory perception, wearable sensors, or machine learning experience\nPrototyping, instrumentation, or soft goods design (textiles, soft robotics, prosthetics)\nBiomechanical modeling/simulation (e.g. OpenSim, FEA) or consumer electronics industry background
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: 244f7e2eb00228a0a2c23148939db980
- Posted 15 hours ago
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