What you will do
Learning a robot to interact with its environment requires true unsupervised learning, perception, planning, active learning, exploration and reinforcement, all ingredients of human learning that are still not well understood. We are looking for an excellent PhD student to join our robotics team and work on novel approaches to perception and control for robots using deep learning.
Fundamental research questions that will be addressed in this thesis are:
- How to train generative perception models in an unsupervised way, combining input from multiple sensors, that can be used for state estimation and planning?
- How to learn control policies, either from demonstrations or from rewards, and transfer these to different setups?
- How to ensure control policies are executed in real-time for enabling closed-loop control?
The research will be conducted in the context of a research project, in collaboration with industry. Besides validating new algorithms in simulation, you also have access to an Industrial IoT lab (http://idlab.technology/infrastructure/industrial-iot-lab/) with various collaborative robotic manipulators (i.e. Franka Panda, Universal Robots UR3) and Autonomous Ground Vehicles (AGV) to benchmark in the real world.
The research group: imec-IDLAB-UGent
IDLab is a research group of Ghent University, as well as a core research group of imec. IDLab performs fundamental and applied research on data science and internet technology and counts over 300 researchers. Our major research areas are machine learning and data mining; semantic intelligence; multimedia processing; distributed intelligence for IoT; cloud and big data infrastructures; wireless and fixed networking; electromagnetics, RF and high-speed circuits and systems.
IDLab is also part of imec, 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 ground-breaking innovation in application domains such as healthcare, smart cities and mobility, logistics and manufacturing, and energy.
Who you are
- You have a degree in Master of Science/Engineering, preferably in Computer Science, Electronics, or (Mathematical) Informatics. Note: to be admissible to the PhD-program, your degree must be equivalent to 5 years of engineering studies (bachelor + master) in the European Union, and you must have a solid academic track record (graduation cum laude or grades in the top 15% percentile). Please do not hesitate to contact us regarding these administrative matters.
- You have a strong interest in one or more of the following domains: deep learning, robotics, perception and planning. Proven experience in one of these domains, e.g. via your master thesis topic or projects, is a plus.
- You have profound programming skills in Python or Java, additional knowledge of C/C++ is a plus.
- Experience with deep learning platforms (e.g. PyTorch, Tensorflow) and robotics platforms (e.g. ROS) is a plus.
- You are interested in and motivated by the research topic and the use case, as well as in obtaining a PhD degree.
- You speak and write English fluently (C1 CEFR level).
- You have good communication skills and you are a team player.
- You have an open mind and a multi-disciplinary attitude.
- You are eligible for a Flemish PhD scholarship (i.e., you have not enjoyed such a scholarship before).
- Apply with motivation letter, scientific resume, abstract of your master thesis, diplomas and detailed academic results (courses and grades), relevant publications, and at least one reference contact. This information, as well as possible questions, must be sent to Prof. Bart Dhoedt at firstname.lastname@example.org.
- After the first screening, suitable candidates will be invited for an interview (also possible via Skype) and may get a small assignment. Applications will be screened as soon as they are received. The position is open until the vacancy is filled.