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Aarhus University

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PhD in Physical AI for Adaptive Robot Manipulation with Tactile Sensing and Robot Foundation Models Aarhus University in Denmark

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded three-year PhD position. Salary and employment terms follow the agreement between the Danish Ministry of Taxation and the Confederation of Professional Unions, with employment at academic staff basic salary grades 4–8. PhD fellows also receive a monthly non-pensionable allowance.

Deadline

Jan 4, 2027

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Country

Denmark

University

Aarhus University

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Keywords

Computer Science
Electrical Engineering
Deep Learning
Tactile Sensing
Robotics
Mechatronics
ML

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About this position

Aarhus University invites applications for a PhD in Physical AI for Adaptive Robot Manipulation within the Department of Electrical and Computer Engineering and the Graduate School of Technical Sciences. The project is part of STORM, or Soft Tactile Memory for Safe Physical-AI Correction of Robotic Foundation Models, funded by the Independent Research Fund Denmark.

The PhD researcher will develop the machine-learning core that enables robotic foundation models to use physical feedback during action execution. Current vision-language-action and world-action models can follow natural-language instructions, but they primarily rely on visual information. STORM aims to give robots a sense of touch, allowing them to detect slipping grasps, deforming fragile objects, or other unsafe contact conditions and correct their behavior while acting.

The research will address how contact representations can be learned from advanced tactile interfaces, including a soft-fluidic tactile skin developed by the University of Southern Denmark. It will also investigate predictive models for short-horizon contact-state evolution under intended policies, and methods for using discrepancies between expected and sensed contact to adapt pretrained foundation policies efficiently while maintaining safety. Evaluation will combine public benchmarks with real-world robotic setups focused on dexterous manipulation of fragile and unseen objects and safe human-robot interaction.

The researcher will join Aarhus University's Adaptive & Agentic AI (A3) Lab, headed by Dr. Behzad Bozorgtabar, and work closely with Professor Ahmad Rafsanjani and the SDU Soft Robotics group. The research environment connects machine learning, Physical AI, robot foundation models, tactile sensing, world models, and online adaptation. The lab publishes in venues including NeurIPS, ICLR, CVPR, and CoRL, and the PhD may include a planned research stay at KTH Royal Institute of Technology in Stockholm.

Funding details

Fully funded three-year PhD position. Salary and employment terms follow the agreement between the Danish Ministry of Taxation and the Confederation of Professional Unions, with employment at academic staff basic salary grades 4–8. PhD fellows also receive a monthly non-pensionable allowance.

What's required

Applicants must have completed or be nearing completion of a master's degree worth 120 ECTS or equivalent in Computer Science, Machine Learning, Artificial Intelligence, Robotics, Electrical or Computer Engineering, or a related quantitative field before the start date. Advanced proficiency in Python and PyTorch is required, together with hands-on experience training, fine-tuning, or adapting modern deep architectures such as Transformers, state-space or sequence models, and diffusion or flow-matching models. Applicants should have a strong foundation in machine learning, deep learning, or computer vision and motivation to work on Physical AI, multimodal tactile sensing, world models, and online adaptation. Experience in robot or policy learning, world models, sequential representation learning, model adaptation or post-training is advantageous. Robotics hardware, grippers, tactile or force sensors, and ROS 2 experience is advantageous but not required for candidates with exceptional machine-learning backgrounds; willingness to conduct physical robot experiments is required. Strong research potential, scientific rigor, reproducibility, open-source contribution, collaboration skills, and excellent written and spoken English are expected.

How to apply

Submit the application through the Aarhus University online recruitment portal before 4 January 2027 at 23:59 CET. Include a one-page statement of interest, CV with publication list and technical project page, bachelor's and master's transcripts and diplomas, and the required project description copied from the announcement and uploaded as a PDF.

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