PhD in Predictive Human Digital Twins for Human-Centred Systems Engineering

Technical University of Denmark; Kongens Lyngby; On-site; DKK 320,000 - 360,000; Full time

Job summary

DTU Construct at the Technical University of Denmark offers a PhD position in human-centred design at the intersection of biomechanics, AI, and systems engineering. You will help build a new research group and develop methods to convert generic musculoskeletal models into personalised Human Digital Twins using sparse wearable data.

The project combines physics-based and data-driven modelling, with experimental validation, software development, and teaching as part of the DTU PhD programme.

Qualifications

• MSc in Biomedical or Mechanical Engineering, Robotics, Computer Science, Applied Mathematics, Engineering Design, or a related field.
• Solid programming skills (e.g. Python, MATLAB, C++).
• Background in simulation, optimisation, machine learning, sensor processing, or parameter estimation.
• Strong interest in computational modelling of humans and human-technology systems.
• Good communication skills in English and the ability to work independently and in a team.
• Experience with musculoskeletal modelling (e.g. OpenSim, AnyBody, SCONE), motion analysis, or wearable sensing is an advantage.

Responsibilities

• Develop and validate methods for personalising musculoskeletal models from sparse sensor data.
• Combine physics-based and data-driven approaches for model calibration and prediction.
• Quantify and reduce the sim2real gap of Human Digital Twins.
• Plan and carry out experimental studies with human participants.
• Implement your methods in open, reusable software.
• Publish your results and collaborate with researchers at DTU and international partners.

Skills

Python

MATLAB

C++

Machine learning

Biomechanics

Education

MSc in Biomedical or Mechanical Engineering

Tools

OpenSim

AnyBody

SCONE

Job description

Are you interested in human-centred engineering at the intersection of biomechanics, artificial intelligence, and systems engineering, and want to build a strong methodological profile, this PhD position offers a unique opportunity – including the chance to help shape a new research group from the start. At DTU Construct, you will develop methods that turn generic musculoskeletal models into personalised Human Digital Twins – based on sparse wearable sensor data instead of costly laboratory measurements or medical imaging – and assess how reliably they predict how a person moves and interacts with technical systems such as collaborative robots or assistive devices. The project is part of building up a new research group in Human-Centred Design within the Human-Centred Systems Engineering activities at DTU Construct. As part of the DTU PhD programme, you will follow PhD-level courses and contribute to teaching.

Responsibilities

Your overall purpose will be to develop and validate methods for personalising biomechanical Human Digital Twins from sparse sensor data, combining physics-based and data-driven approaches and quantifying the gap between simulation and reality (sim2real).

Primary tasks

• Develop methods for personalising musculoskeletal models from sparse multimodal sensor data.
• Combine physics-based and data-driven approaches for model calibration and prediction.
• Quantify and reduce the sim2real gap of Human Digital Twins.
• Plan and carry out experimental studies with human participants.
• Implement your methods in open, reusable software.
• Publish your results and collaborate with researchers at DTU and international partners.

Qualifications

We are looking for a motivated candidate with:

• An MSc in Biomedical or Mechanical Engineering, Robotics, Computer Science, Applied Mathematics, Engineering Design, or a related field.
• Solid programming skills (e.g. Python, MATLAB, C++).
• A background in simulation, optimisation, machine learning, sensor processing, or parameter estimation.
• A strong interest in computational modelling of humans and human-technology systems.
• Good communication skills in English and the ability to work both independently and in a team.
• Experience with musculoskeletal modelling (e.g. OpenSim, AnyBody, SCONE), motion analysis, or wearable sensing is an advantage.

We do not expect you to master all of these areas – a solid foundation and the motivation to grow into the field matter most.