The department of AI at the Donders Institute is recruiting two postdoctoral researchers on a new project called SPIKEFERENCE, co-funded by the Human Brain Project. They will work under the supervision of Pablo Lanillos, Serge Thill and Marcel van Gerven. 
The SPIKEFERENCE project aims to control industrial robots with spiking neural networks using neuroscience-inspired algorithms (deep active inference), providing adaptation and conditional hierarchical problem-solving. The outcome of the project will be a step forward in brain-inspired computational models, both theoretically and experimentally, bridging the gap between low-level control and neurosymbolic approaches, contributing to major challenges within the Human-Brain Project, such as the development of neuroscience-driven adaptive cognitive architectures, and providing novel spike-driven closed-loop controllers that can be deployed in real robots.

This postdoctoral researcher position (deep learning profile) is framed in a new promising line of research within neuroscience-inspired artificial intelligence linked to adaptation and improvisation. Starting from our current deep active inference models, you will develop novel algorithms for robot perception and action by combining ideas from state representation learning, variational inference and functional models of the brain.. Initial prototyping and validation will take place in simulation (ROS-Gazebo and Neurorobotics platform). You will work in close collaboration with your supervisors, other postdoctoral researchers, and a PhD candidate.

Furthermore, you will join an exciting and vibrant young team of experts in machine learning, artificial intelligence and neurocomputing. As we support the Human Brain Project's equal opportunities policy, we strongly encourage submissions from various representative minorities.

Essential: 

• A PhD in a relevant discipline.
• Good mathematical skills.
• Good knowledge of deep learning and probabilistic approaches.
• Knowledge of any of the following topics: active inference, predictive coding, state representation learning, reinforcement learning.

Desirable: 

• Previous experience in one of the following areas (or related topics): variational inference, control as inference, world models, neurosymbolic approaches.
• Previous experience with attentional/gating mechanisms.
• Familiarity with robot estimation and control.
• Familiarity with brain-inspired computing.

Fixed-term contract: Fixed term: 22 months (max until 31 March 31 2023).

• Employment: 1.0 FTE.
• A maximum gross monthly salary of € 5,127 based on a 38-hour working week (salary scale 11).
• The exact salary depends on the candidate's qualifications and amount of relevant professional experience.
• In addition to the salary: an 8% holiday allowance and an 8.3% end-of-year bonus.
• Duration of the contract: fixed term: 22 months (until 31 March 2023).
• The intended start date is 1 June 2021.
• You will be able to use our Dual Career and Family Care Services. Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment  and help your family settle in Nijmegen.
• Have a look at our excellent employment conditions. They include a good work-life balance (among other things because of the excellent leave arrangements), opportunities for development and a great pension scheme.

Radboud University

We want to get the best out of science, others and ourselves. Why? Because this is what the world around us desperately needs. Leading research and education make an indispensable contribution to a healthy, free world with equal opportunities for all. This is what unites the more than 22,000 students and 5,000 employees at Radboud University. And this requires even more talent, collaboration and lifelong learning. You have a part to play!

Faculty of Social Sciences

You will join the Donders Institute for Brain, Cognition and Behaviour and the Department of Artificial Intelligence at Radboud University (Nijmegen, Netherlands). You will have the opportunity to collaborate and interact with renowned experts in the fields of artificial intelligence, psychology and neuroscience and benefit from an exciting and expanding research environment around the newly started ELLIS Nijmegen unit.

The Donders Institute for Brain, Cognition and Behaviour is a world-class interfaculty research centre, housing more than 700 researchers devoted to understanding the mechanistic underpinnings of the human mind. Research at the Donders Institute is focused on four themes: 1. Language and communication, 2. Perception, action and control, 3. Plasticity and memory, 4. Neural computation and neurotechnology. Excellent, state-of-the-art research facilities are available for the broad range of neuroscience research that is being conducted at the Donders Institute. The Donders Institute has been assessed by an international evaluation committee as excellent and recognised as a ‘very stimulating environment for top researchers, as well as for young talent’. The Donders Institute fosters a collaborative, multi-disciplinary, supportive research environment with a diverse international staff. English is the lingua franca at the Institute.

The Department of Artificial Intelligence focuses on the development of human-like AI systems and new intelligent technology to improve human-machine interaction. Our group investigates the computational principles underlying natural intelligence and uses these principles to develop more capable and efficient intelligent machines. The department is responsible for the highly successful educational programme in cognitive AI, which currently hosts about 600 AI students and is one of the initiators of Radboud AI, which aims to develop the next generation of responsible AI systems. The department also operates the RobotLab which hosts several state-of-the-art platforms, including humanoid robots (Pepper, Nao) and industrial arms (UR5e), and has significant computational resources at its disposal for developing deep learning models and simulating spiking neural networks, including GPU clusters and Nengo BrainBoard FPGAs.