Research Intern: Industrial ML & Digital Twins

Eidgenössische Technische Hochschule Zürich; Zürich; Vor Ort; CHF 27.900 - 42.408; Vollzeit

Zusammenfassung

inspire AG, in collaboration with ETH Zurich, seeks a machine learning engineer to develop cutting-edge AI algorithms for digital twin applications in real-world industrial systems. You will build digital twins, collect datasets from real hardware, and deploy control policies for industrial processes.

The role emphasizes hands-on ML, time-series forecasting, and modelling, with collaboration across a research group focused on robotics and automation.

Qualifikationen

• Pursuing a master’s degree (university) in robotics, electrical or mechanical engineering, or CS.
• Practical knowledge of time series modelling, seq2seq, and data‑driven digital twin models (e.g., Transformers, Mamba, LSTMs) with applications in industry.
• Knowledge/courses taken on estimation theory, network modeling, and graph theory are a plus.
• Excellent coding skills in python, ROS, and ML pipeline experience on simulator and training libraries.
• Good foundation in linear algebra, numerical methods, optimization, and control theory.
• An excellent knowledge (written/oral) of English is a must. Knowledge of German is beneficial.

Aufgaben

• Develop customized Digital Twins for industrial applications using ML from real data
• Develop and maintain the codebase to support various training modules and libraries
• Collaborate with our industrial partner and collect extensive datasets on real hardware
• Design and deploy control policy on industrial applications

Kenntnisse

Time series modelling

Seq2seq

Digital twin models

Transformers

LSTMs

Python

ROS

ML pipeline

Linear algebra

Optimization

Control theory

English proficiency

Ausbildung

Master's degree candidate in robotics / electrical / mechanical engineering / CS

Tools

Python

ROS

Jobbeschreibung

inspire AG, in collaboration with ETH Zurich, seeks a machine learning engineer to develop cutting-edge AI algorithms for digital twin applications in real-world industrial systems. You will build digital twins, collect datasets from real hardware, and deploy control policies for industrial processes.

The role emphasizes hands-on ML, time-series forecasting, and modelling, with collaboration across a research group focused on robotics and automation.