7 beste Stellen als controller in muri ag – aktuell auf Personalsuche

Locomotion & Whole-Body Control Engineer (human)
Neura Robotics —Zürich, ZH
- 100%
- Doktorat
- Master
- C++
Direkt bewerben
13 Tage
Robot Platform Engineer (Mensch)
Neura Robotics —Zürich, ZH
- 100%
- C++
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9 Tage
AI Engineer - Dexterous Manipulation
Flexion Robotics —Zürich, ZH
- 100%
- Doktorat
- Master
- Python
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Citrix NetScaler Engineer 100% (f/m/d)
Julius Baer —Zürich, ZH
- 100%
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- Englisch
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AI Research Engineer - Dexterous Manipulation (Egocentric Models)
Flexion Robotics —Zürich, ZH
- Doktorat
- Master
- Python
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System Engineer
Auterion —Zürich, ZH
- Master
- C++
- Bachelor
- Eltern-/Erziehungsurlaub
- Pensionskasse
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Controller (m/w/d) 60 - 80 %
DHL —Regensdorf, ZH
- Teilzeit
- Microsoft Excel
- Englisch
- Bachelor
- Eltern-/Erziehungsurlaub
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controller jobs near muri ag

Locomotion & Whole-Body Control Engineer (human)

Neura Robotics -
Zürich, ZH

Direkt bewerben

Details zur Stelle

100%
vor 13 Tagen

Qualifikationen

Doktorat
Master
C++
Python
Debugging

Vollständige Stellenbeschreibung

Your mission & challenges

We are growing our legged-robotics capability on NEURA's humanoid (4NE-1) and quadruped platforms. This role spans both core layers of the legged control stack: trajectory optimization and MPC for kino-dynamic motion generation, and QP-based instantaneous whole-body control for executing those motions on real hardware at 1 kHz.

The work is focused on contact-rich dynamics, real-time optimization, and reliable execution on physical robots. You will collaborate closely with state estimation, simulation, low-level control, and hardware stakeholders, and with the application teams whose tasks ultimately depend on robust, predictable locomotion and whole-body behaviour.

Whole-body motion generation and control for floating-base legged platforms — locomotion, balance, contact transitions, and loco-manipulation (walking while manipulating).
Trajectory optimization and model-predictive control pipelines over robot state, contact schedules, ground reaction forces, centroidal momentum, and joint trajectories — using reduced-order locomotion models such as LIPM, SRBD, and centroidal dynamics.
QP-based task-space inverse dynamics for executing instantaneous whole-body control from MPC and trajectory-optimization references at 1 kHz on the real robot.
Whole-body modelling for the platform: floating-base rigid-body dynamics from URDF / MJCF, joint configuration, FK / IK, Jacobians, and mass / Coriolis / gravity computation.
Constraint formulation across the MPC and QP layers — contact, friction, torque, joint, kinematic, and stability constraints — with task-hierarchy design appropriate to the platform.
Solver performance work across both layers: warm-starting, numerical conditioning, constraint handling, and real-time reliability at 500 Hz – 1 kHz.
Deployment, tuning, and debugging of MPC, trajectory optimization, IK, and inverse dynamics pipelines on physical robots — including platform-specific contact-model calibration and validation against real robot data.
High-performance C++ for real-time execution; Python tooling for analysis, prototyping, and debugging.

What we can look forward to

MSc or PhD in robotics, controls, mechanical or electrical engineering, computer science, or a related field.
4+ years of hands-on experience developing trajectory optimization, MPC for locomotion, and / or whole-body control on physical robots.
Strong foundation in floating-base articulated rigid-body dynamics and contact modelling.
Strong working knowledge of reduced-order locomotion models (LIPM, SRBD, centroidal dynamics, or equivalents) and their use inside MPC.
Strong foundation in optimal control, constrained numerical optimization, and model-predictive control for legged robots.
Hands-on experience with whole-body QP / TSID frameworks on real robot data — including QP / DDP solver internals.
Hands-on experience deploying real-time control / MPC / WBC pipelines at 500 Hz – 1 kHz on hardware.
Strong C++ for real-time robotics software; Python for analysis, tooling, prototyping, and debugging.
Practical understanding of how contact dynamics, actuator limits, latency, state-estimation error, solver failure modes, and model mismatch behave on real hardware.
A collaborative working style: shared design, constructive code review, proactive communication, and reliable coordination across control, estimation, simulation, low-level control, and hardware disciplines. Strong teamwork is essential for this role.

Nice to Have

Hands-on experience on humanoids, quadrupeds, or other high-DOF legged robots.
Familiarity with Pinocchio, MuJoCo, Crocoddyl, IPOPT, TSID, OCS2, or similar open-source tools.
Hierarchical QP, weighted QP, task prioritization, contact force optimization, or operational-space control.
Contact planning, gait optimization, balance recovery; CPG-based or hybrid CPG / MPC controllers.
Multi-contact WBC: foot contact, bimanual grasping, or base-arm coordination.
Contact-consistent dynamics and impact-aware control transitions.
Experience with torque-controlled robots and high-bandwidth electric actuation.
Publications at RSS, ICRA, IROS, or CoRL in legged locomotion or whole-body control.

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