PhD Vacancy in Artificial Intelligence for Graph Evolution Prediction

IMEC

​imec is the world-leading research and innovation hub in nanoelectronics and digital technologies. The combination of our widely acclaimed leadership in microchip technology and profound software and ICT expertise is what makes us unique. By leveraging our world-class infrastructure and local and global ecosystem of partners across a multitude of industries, we create groundbreaking innovation in application domains such as healthcare, smart cities and mobility, logistics and manufacturing, and energy.

As a trusted partner for companies, start-ups and universities we bring together close to 3,500 brilliant minds from over 70 nationalities. Imec is headquartered in Leuven, Belgium and also has distributed R&D groups at a number of Flemish universities, in the Netherlands, Taiwan, USA, China, and offices in India and Japan. All of these particular traits make imec to be a top-class employer.

University of Antwerp – imec IDLab Research group

The Internet & Data Lab (IDLab) is an imec research group at the University of Antwerp and Ghent University. IDLab focuses its research on internet technologies and data science. IDLab is a joint research initiative between Ghent University and the University of Antwerp. Bringing together 300 internet experts, we develop technologies outperforming current solutions for communication subsystems, high speed and low power networking, distributed computing and multimedia processing, machine learning, artificial intelligence and web semantics. Within Antwerp, where you will work, the overall IDLab research areas are machine learning and wireless networking. IDLab has a unique research infrastructure used in numerous national and international collaborations.

IDLab collaborates with many universities and research centres worldwide and jointly develops advanced technologies with industry (R&D centers from international companies, Flanders’ top innovating large companies and SME’s, as well as numerous ambitious startups).

For further development of the IDLab AI Applications team in the machine learning cluster, we are looking for a PhD candidate in Artificial Intelligence for process control in domains such as chemical engineering, water treatment and HVAC.

The AI Applications team aims to bring state-of-the-art machine learning methods to industry, bridging the gap between fundamental research and industrial applications. The team researches in areas such as data-driven modeling, deep learning and reinforcement learning to tackle real life problems. Our goal is to make AI safely and reliably applicable in industrial scenarios, where it should complement, enhance or replace the state of the art in complex control scenarios where current techniques fail to deliver. The team applies its AI solutions in domains such as chemical engineering, autonomous shipping, beyond-5G wireless communication, traffic management and logistics, in collaboration with key industry partners in their respective domains.

The job

Recently, graph neural networks gained increasing popularity in domains such as social networks, urban road infrastructure, health science, or even inland waterways. Within our research group, we investigate how graph structures evolve using Spatio-temporal graph neural networks. Furthermore, the knowledge learned in a graph should be transferred to different graphs. Mechanics such as attention, encoding, embeddings, or external features are used within graph neural networks. In this research track, you will start with a state-of-the-art solution created at IDLab and further push the state-of-the-art in graph neural network research.

You interact and collaborate on a technical level with research partners, and will deploy your models in industrially relevant environments.

• In the context of graph neural networks, you will conduct academic research on Machine Learning and Deep Learning techniques to improve graph evolution prediction.
• You will research data-driven methodologies to extract knowledge from both a spatial and temporal point of view.
• You will develop novel graph neural networks allowing for short-term predictions as well as long-term predictions of the graph features (e.g. traffic, estimated time of arrival, etc.).
• You prepare a Ph.D. dissertation on deep learning using spatio-temporal graph neural networks.
• You publish and present results both at international conferences and in scientific journals.
• You contribute to national and international research projects in collaboration with key players in the industry.

• You have (or will receive within a few months) a Masters of Science degree, preferably in Computer Science, Engineering, Mathematics, Physics, or related fields.
• You are fluent in python, machine learning, and deep-learning tools.
• You are comfortable in modelling complex applications using data-driven and ML perspectives in mind.
• You have a keen interest in deep learning and data-driven modeling.
• Having prior knowledge of convolutional neural networks, recurrent neural networks, and fully connected neural networks is an advantage.
• Having published in high-ranking conferences and journals in the field is an advantage.
• You know how to prioritize and can deliver in time.
• You are well-organized and able to autonomously plan and execute tasks.
• You are a team player and have strong communication skills.
• Your English is fluent, both speaking and writing.