Artificial Intelligence (AI) empowers many applications in virtually all aspects of life. More and more devices, machines, and sensors connect to the Internet of Things (IoT), which creates large amounts of data. Even fast networks sometimes struggle to transfer data to a data centre or the ‘cloud’ for analysis, demanding incredible power. Solving this high energy consumption and connectivity crisis is only possible by developing intelligent hardware for edge-computing systems, allowing for decentralized data processing close to a machine, device, or IoT sensor. To this end, the NWO IMAGINE project strives to design a novel and innovative CMOS-compatible energy-efficient framework for sensing and computing for vision edge-AI applications. IMAGINE will co-design device technology, analogue and digital electronic circuitry, algorithms, and systems to empower many applications, from reactive systems and autonomous driving to industrial inspection. IMAGINE is a collaboration of the University of Twente, the Eindhoven University of Technology, Toyota and IMEC.

We invite applications for a PhD position at the Computer Architecture for Embedded Systems group. We are looking for a talented and highly motivated candidate to work on this collaborative project doing research at the intersection of computer architecture, design of memory subsystems, FPGA-based acceleration, and deep learning.

• You are an enthusiastic and highly motivated researcher.
• You have a master’s degree in a relevant discipline, such as computer engineering, embedded systems, or computer science.
• You have good knowledge of C, C++, and Python (preferably in Linux environment).
• You have experience in FPGA design using hardware description languages and/or high-level synthesis (VHDL, Verilog, Vitis HLS, Vitis), and knowledge in programming FPGA boards.
• You know about machine learning and deep learning, and previous experience with AI/ML frameworks, such as TensorFlow and PyTorch
• You are proficient in English.

• As a PhD student at UT, you will be appointed to a full-time position for four years, with a qualifier in the first year, within a stimulating scientific environment.
• The University offers a dynamic ecosystem with enthusiastic colleagues.
• Your salary and associated conditions are in accordance with the collective labour agreement for Dutch universities (CAO-NU).
• You will receive a gross monthly salary ranging from € 2,770 (first year) to € 3,539 (fourth year);
• There are excellent benefits including a holiday allowance of 8% of the gross annual salary, an end-of-year bonus of 8.3%, and a solid pension scheme.
• Free access to sports facilities on campus.
• A family-friendly institution that offers parental leave (both paid and unpaid);
• You will have a training programme as part of the Twente Graduate School where you and your supervisors will determine a plan for a suitable education and supervision.
• We encourage a high degree of responsibility and independence while collaborating with close colleagues, researchers and other staff

The CAES group conducts research and education in computer architecture and computing systems with a particular emphasis on embedded systems.

Embedded systems are already commonplace, they provide the necessary control and integration of cyber-physical systems. In the last couple of decades, a larger portion of the world’s total computing power is taking place at the edge, motivated by broad concepts, such as the Internet-of-Things (IoT), machine learning, smart grids, and real-time and dependable systems. With different constraints in terms of power consumption, performance, reliability, and security, the understanding of the underlying computer architectures is vital for the efficient integration of these systems.

Our research goal is to investigate the challenges and opportunities in the intersection between CS and EE. This large scope allows our researchers to tackle real problems with a broad and systemic view, allowing for the development of new technologies, architectures, design automation tools, algorithms, methodologies, and models. This process requires knowledge from different domains in the hardware and software levels of abstraction, allowing ample space for our members to develop and collaborate internally and with external partners.