Postdoc Position: Adaptive and Distributed Foundation Model Inference across the Computing Continuum

Aarhus University; Aarhus; On-site; DKK 420,000 - 520,000; Full time

Job summary

Aarhus University invites applications for a 2-year postdoctoral position in Adaptive and Distributed Foundation Model Inference across the Computing Continuum. The candidate will advance resource-efficient, distributed inference leveraging edge and cloud resources, working within a dynamic research group at ECE AU.

The role focuses on distributed inference, MoE placement, and inference optimization, with opportunities to publish in top venues and collaborate with academic and industry partners

Qualifications

• PhD in Computer Science, Computer Engineering, Electrical Engineering or a related field.
• Strong background in Deep Learning (e.g., Transformers, foundation models).
• Strong programming skills in Python and experience with deep learning frameworks (e.g., PyTorch).
• Experience with distributed systems and edge AI.
• Strong publication record in reputable conferences or journals relative to career stage.
• Excellent written and spoken English communication skills.

Responsibilities

• Contribute to distributed foundation model inference research across the computing continuum.
• Develop and evaluate distributed inference strategies and MoE placement for acceleration.
• Investigate token compression and feature compression for efficient inference.
• Publish results and collaborate with partners within Horizon Europe project.

Skills

PhD in Computer Science/Engineering

Deep learning (Transformers)

Python

PyTorch

Distributed systems

English communication

Education

PhD in CS/CE/EE or related

Tools

PyTorch

Python

Job description

Institut for Elektro- og Computerteknologi - Communication, Control and Automation - Fakultet: Technical Sciences

Postdoc Position: Adaptive and Distributed Foundation Model Inference across the Computing Continuum

Institut for Elektro- og Computerteknologi - Communication, Control and Automation Helsingforsgade 10 8200 Aarhus N

We are seeking highly motivated and talented applicants for a 2-year postdoctoral position (with the possibility of extension) in the area of distributed foundation model inference.

Join us at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing resource-efficient and distributed foundation model inference across the computing continuum, leveraging the computation resources at Edge and Cloud. Our research aims to enable scalable, low-latency, and resource-aware deployment of large foundation models.

Expected start date and duration of employment

This is a full-time, fixed-term position for two years, starting on March 1, 2027, or as soon as possible thereafter.

The initial appointment will run until Feb 28, 2029, or for 24 months from the actual start date.

• The successful candidate will contribute to cutting-edge research on topics including:
• Distributed and collaborative inference strategies;
• Mixture-of-Experts (MoE) placement and scheduling for inference acceleration;
• Token compression or Intermediate feature compression;
• Resource-aware and communication-efficient inference optimization.

You will work in a dynamic and collaborative research environment, with opportunities to publish in top-tier venues and collaborate with leading academic and industry partners within the Horizion Europe Project.

Your profile

We are looking for a highly motivated and talented candidate with a background in deep learning. The required qualifications include:

• Ph.D. in Computer Science, Computer Engineering, Electrical Engineering or a related field;
• Strong background in Deep Learning (e.g., Transformers, foundation models);
• Strong programming skills in Python and experience with deep learning frameworks (e.g., PyTorch);
• Experience with distributed systems and edge AI;
• Strong publication record in reputable conferences or journals relative to career stage;
• Excellent written and spoken English communication skills.

Following qualifications will be considered as an advantage:

• Experience in working with stream data;
• Experience with collaborative, cross-cultural research environments.

Who we are

You will be based at the Department of Electrical and Computer Engineering (ECE) at Aarhus University, a dynamic and growing department committed to excellence in research, education, and innovation. Our research spans Internet of things, machine learning, signal processing, to digital twins, all with a strong emphasis on high impact research and societal relevance.

This position will be supervised by Professor Qi Zhang, whose current research focuses on Edge Intelligence, Distributed Foundation Model inference, Internet of Things and Analytics on compressed data.

What we offer

We offer a vibrant and inclusive research environment with a clear commitment to real-world impact. Denmark is consistently ranked among the best countries in the world for work-life balance and quality of life. Family-friendly policies include generous parental leave, subsidised childcare, and access to excellent public healthcare and education. As a postdoc at Aarhus University, you will benefit from a supportive and flexible workplace culture that values diversity and offers excellent conditions for researchers and their families.

Specifically, we offer:

• Access to state-of-the-art facilities and computing infrastructure;
• Strong support for research career development, including mentoring and international networking opportunities;
• A commitment to diversity, equity, and inclusion in all aspects of our work;
• A workplace characterised by professionalism, equality and a healthy work-life balance.

Place of work and area of employment

The place of work is Helsingforsgade 10, 8200 Aarhus N, and the area of employment is Aarhus University with related departments.

Contact information

For further information, please contact: Professor Qi Zhang, [phone], [e-mail].

Deadline

Applications must be submitted by December 6th, 2026.

Technical Sciences refers to the Ministerial Order on the Appointment of Academic Staff at Danish Universities under the Danish Ministry of Science, Technology and Innovation .

The application must be in English and include a curriculum vitae, degree certificate, a complete list of publications, a statement of future research plans and information about research activities, teaching portfolio and verified information on previous teaching experience (if any). Guidelines for applicants can be found here.

Appointment shall be in accordance with the collective labour agreement between the Danish Ministry of Taxation and the Danish Confederation of Professional Associations.

Further information on qualification requirements and job content may be found in the Memorandum on Job Structure for Academic Staff at Danish Universities .

Salary and terms as agreed between the Danish Ministry of Taxation and the Confederation of Professional Unions at basic salary steps 4-8.

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants.

Research activities will be evaluated in relation to actual research time. Thus, we encourage applicants to specify periods of leave without research activities, in order to be able to subtract these periods from the span of the scientific career during the evaluation of scientific productivity.

Aarhus University offers a broad variety of services for international researchers and accompanying families, including relocation service and career counselling to expat partners. Read more here . Please find more information about entering and working in Denmark here .

Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here .