Doctoral student in Multi-Modal Environment Modeling for Wireless Spatial Intelligence

Offer Description

Electrification and digitalisation are among the largest areas for the future in the conversion to sustainable societies. The Department of Electrical Engineering conducts successful research and education in the areas - renewable energy sources, electric vehicles, industrial IoT, 6G communication and wireless sensor networks as well as research and education within life science, smart electronic sensors and medical systems. The Department of Electrical Engineering is an international workplace with around 170 employees that all contribute to important technical energy and health challenges at the Ångström Laboratory.

The position will be at the Division of Signals and Systems, Department of Electrical Engineering.

Project topic: Multi-Modal Environment Modeling for Wireless Spatial Intelligence

Project description: Future wireless networks are expected to evolve beyond communication infrastructures into intelligent systems capable of perceiving, understanding, and interacting with the physical world. This project focuses on developing model- and learning-based methods for wireless localization, integrated sensing and communication (ISAC), and multi-modal environment modeling by combining wireless measurements with complementary information (e.g., vision, geometry, maps, and other sensing modalities). The project aims to develop foundational theories, algorithms, and system architectures for wireless spatial intelligence, enabling wireless networks to construct semantic multi-modal representations of physical environments.

The project will investigate how distributed wireless devices can collaboratively learn, maintain, and exchange these semantic representations to support cooperative perception, localization, sensing, and environment understanding. The developed methods will provide a foundation for next-generation wireless systems capable of ISAC, environment-aware communication, prediction, autonomous network optimization, and digital-twin-enabled decision-making.

The doctoral student will develop novel theories, algorithms, and AI models through mathematical analysis, simulation, and experimental validation. The position also offers opportunities for research visits and internships at leading universities, research institutes, and industrial partners through the project's international collaboration network.

Duties:

The doctoral student's primary responsibility is to conduct research on AI-native wireless spatial intelligence. The research will include:

• developing multi-modal representations of physical environments by integrating wireless, visual, geometric, and map-based observations;
• learning radio and electromagnetic primitives for constructing semantic representations of physical environments;
• designing collaborative perception and semantic information sharing mechanisms for cooperative wireless devices and intelligent agents;
• developing models and algorithms for multi-modal-aided wireless localization, 3D reconstruction, and environment understanding;
• designing differentiable rendering, simulation, and learning pipelines for wireless world models;
• studying identifiability, uncertainty quantification, robustness, and generalization across scenarios and frequency bands;
• validating the developed methods through simulation and, where appropriate, experimental demonstrations.

The duties also include completing doctoral coursework, publishing research in leading international journals and conferences, presenting results at project meetings and workshops, and contributing to international research collaborations.

The duties further include participation in teaching and other departmental tasks, corresponding to a maximum of 20 % of the working time.

Qualification requirements:

• Master of Science in Engineering, or a foreign degree deemed equivalent, in Electrical Engineering, Computer Science, or related fields.
• Strong knowledge in at least two of the following fields: wireless communications, signal processing, statistical inference, optimization, machine learning, computer vision, and robotics.
• Experience in one or more of the following areas is highly desirable: 5G/6G communication systems, integrated sensing and communication (ISAC), wireless localization and sensing, radio propagation, SLAM, scene understanding, embodied AI, multimodal learning, physics-informed machine learning, generative AI, or world models.
• Excellent command of spoken and written English. Applicants are encouraged to provide English language test scores (e.g., TOEFL or IELTS), if available.
• Strong programming skills in Python. Experience with scientific computing and machine-learning frameworks such as PyTorch and TensorFlow.

We place great emphasis on personal qualities such as excellent analytical thinking, curiosity, creativity, independence, and communication skills, with the ability to conduct interdisciplinary research both independently and collaboratively.

Qualifications desired:

• Publications in leading journals and conferences in relevant fields.
• Experience with modern AI frameworks, simulation platforms, experimental research, measurement campaigns, or prototype development.
• Demonstrated technical excellence through research competitions, open-source software contributions, or major project experience.

About the employment:

Fixed term position 48 months, in accordance with Chapter 5, Section 7 of the Higher Education Ordinance. Full-time. Start date 2027-03-01 or as agreed. Location: Uppsala.

Rules governing doctoral students are set out in the Higher Education Ordinance Chapter 5, Sections 1-7 and in Uppsala University's rules and guidelines.

Application: The application should include: (a) a brief description of your research interests and relevant experience (maximum 2 pages), (b) a CV, (c) copies of diplomas and certificates, (d) your thesis (or a draft thereof), and (e) other relevant documents. Applicants are encouraged to provide the contact information of two academic referees.

Benefits: Doctoral students in Sweden are full-time employees of the university and receive pension contributions, comprehensive social benefits, generous parental leave, and paid annual vacation.

We offer a stimulating research environment shaped jointly by the doctoral student and the research team. The doctoral student will be supervised by at least two supervisors. The Department of Electrical Engineering also provides a salary supplement in addition to the local guidelines for doctoral students at Uppsala University.

Read more about our benefits and what it is like to work at Uppsala University

For further information about the position, please contact:
Hui Chen, hui.chen@angstrom.uu.se
Subhrakanti Dey, subhrakanti.dey@angstrom.uu.se

You are welcome to submit your application no later than November 30, 2026. UFV-PA 2026/2989.

Where to apply

Website: https://uu.varbi.com/en/what:job/jobID:975824/type:job/where:39/apply:1

Requirements

• Research Field: Engineering
• Education Level: Master Degree or equivalent
• Research Field: Engineering
• Years of Research Experience: None

Work Location(s)

• Number of offers available: 1
• Company/Institute: Uppsala universitet
• Country: Sweden
• City: Uppsala

Contact

• City: Uppsala
• Website: http://www.uu.se/en/about-uu/join-us/jobs/