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

Communication, Control and Automation; Aarhus; Vor Ort; DKK 420.000 - 480.000; Vollzeit

Zusammenfassung

Aarhus University’s Department of Electrical and Computer Engineering invites applications for a 2-year postdoctoral position in adaptive and distributed foundation model inference across the computing continuum. The role focuses on resource-aware, edge-to-cloud inference and scalable deployment of large foundation models.

You will work with Prof. Qi Zhang on MoE placement, token compression, and distributed inference strategies, contributing to cutting-edge research and publishing in top venues.

Qualifikationen

• PhD in computer science, electrical engineering, or related field.
• Strong background in deep learning and transformers.
• Proficient in Python and PyTorch.
• Experience with distributed systems and edge computing.
• Strong publication record and excellent English communication.
• Experience with stream data or collaborative research environments is a plus.

Aufgaben

• Contribute to distributed foundation model inference research.
• Work on Mixture-of-Experts placement and scheduling for inference acceleration.
• Investigate token or feature compression for efficiency.
• Advance resource-aware and communication-efficient inference.

Kenntnisse

PhD in Computer Science

Deep Learning

Python

PyTorch

Distributed systems

Publications

English proficiency

Ausbildung

PhD in Computer Science / Electrical Engineering / related field

Tools

PyTorch

Jobbeschreibung

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

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 one year, 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.

Job description

• 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.

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.

Formalities and salary range

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.

Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU.

Om Aarhus Universitet

Aarhus Universitet er et fagligt bredt og forskningsintensivt universitet med høj kvalitet i uddannelse og forskning, og et stærkt engagement i samfundsudviklingen nationalt og globalt. Universitetet tilbyder et inspirerende uddannelses- og forskningsmiljø for 37.500 studerende inklusive ph.d.-studerende og har 9.000 medarbejdere opgjort i årsværk samt en årlig omsætning på 8,9 mia. kr. Læs mere på au.dk.