Senior Control Engineering Lead in Prosthetics and Orthotics (d/f/m)

Summary Statement

The Global Research Hub Germany at Ottobock is seeking an experienced Senior Control Engineering Lead in Prosthetics and Orthotics (d/f/m) to lead a dedicated research group focused on next-generation control strategies for prosthetics and orthotics. Our department sits at the intersection of mechatronics, biomechanics, and human-machine interaction, and is committed to developing technologies that measurably improve the quality of life for people with mobility impairments.

This role is an opportunity to apply methods developed for demanding dynamic systems to one of the most impactful challenges in healthcare: help people maintain or regain freedom of movement and autonomy through intelligent assistive devices.

The position is located in our headquarter in Duderstadt near Göttingen.

Duties & Responsibilities

• Take responsibility for a cross-project specialized topic on a global level
• Lead projects on the topic of control and sensing for prosthetic and orthotic devices; scope research projects, define individual objectives, coordinate timelines, and ensure quality of output
• Develop and maintain a multi-year research roadmap aligned to the department’s and broader technology vision; represent the group in departmental and cross-functional planning processes as well as externally
• Advise internal partners and identify, initiate, and manage collaborations with external academic institutions and technology partners; contribute to grant applications and joint research programs where relevant
• Investigate, design, and validate novel control architectures for lower- and upper-limb prosthetics and orthotics, integrate classical methods (model predictive control, impedance/admittance control, observer design) with AI/ML techniques (reinforcement learning, recurrent networks, data-driven system identification)
• Develop and apply state estimation methods , including nonlinear Kalman filter variants, sensor fusion, and neural observers, to accurately characterise user intent, limb state, and terrain context from on-device sensor data
• Design and coordinate experimental validation studies, including human subject testing under relevant protocols; analyse and interpret results and iterate on control designs accordingly
• Evaluate and integrate intelligent sensor technologies (IMUs, EMG, force/torque, soft sensors) into control pipelines; assess signal quality, latency, and robustness requirements relevant to patient use
• Benchmark control performance against state of the art; track competitor developments and emerging methodologies in wearable robotics, human-robot interaction, and assistive technology
• Collaborate with product development, biomechanics, and clinical affairs teams to ensure research outputs are grounded in real user needs and compatible with regulatory and safety requirements (EU MDR, EU AI Act)
• Prepare technical reports, and present results to internal leadership and external partners
• Contribute to intellectual property processes including patent assessments and invention disclosures

Qualifications

• PhD (or equivalent research experience) in Control Engineering, Mechatronics, Robotics, Electrical Engineering, or a closely related field
• Minimum 5 years industry experience in control systems development for dynamic, safety-critical applications
• Demonstrated experience leading or co-leading a research team, project group, or multi-person technical workstream
• Advanced proficiency in nonlinear control design and analysis: model predictive control, impedance/admittance control, robust and adaptive control, stability analysis for time-varying systems
• Strong background in state estimation for nonlinear systems: Unscented Kalman Filter (UKF), Extended Kalman Filter (EKF), particle filters, or equivalent Bayesian estimation methods
• Demonstrated ability to integrate AI/ML methods into control or estimation pipelines: recurrent neural networks for dynamics modelling, convolutional or classification networks for context recognition, reinforcement learning for policy optimisation
• Experience with system identification techniques, both model-based (frequency domain, parameter estimation) and data-driven (neural observers, regression models), applied to real hardware
• Proficiency in MATLAB/Simulink for modelling and controller design; familiarity with Python-based ML frameworks (PyTorch, TensorFlow, or equivalent) for AI-integrated pipelines
• Practical experience designing and running experimental validation studies on physical mechatronic systems under realistic operating conditions
• Strong systems-engineering mindset: able to move between mathematical formalism and implementation-level constraints without losing rigour
• Collaborative and interdisciplinary orientation; comfortable working with biomechanists, clinical partners, software engineers, and product developers as peers
• Clear and precise communicator in technical and non-technical contexts; able to present complex control concepts to varied audiences including clinicians and device users
• High degree of intellectual curiosity and willingness to engage with a new application domain; prior experience in wearable robotics, orthotics, or prosthetics is advantageous but not required
• Proficiency in English (working language of the department) and German language

Benefits

• Competitive compensation package
• days of vacation
• Flexibility: Flexible work hours and the opportunity for remote work
• Retirement benefits: Company pension plan, capital-forming benefits
• Health and well-being: EGYM Wellpass, company sports (e.g., yoga, volleyball, tennis), external counseling for personal and professional matters
• Mobility: Carpooling platform, access to the company vehicle pool for business trips, bicycle leasing (JobRad & Bikeleasing)
• Discounts & perks: Corporate benefits and offers from local partners
• Onboarding & professional development: Personalized onboarding during the Ottobock Welcome Days & training opportunities at the Ottobock Academy