The Eindhoven Artificial Intelligence Systems Institute (EAISI) is funding 2 PhD positions for the highly innovative
BayesBrain project, in collaboration with the departments of
- Mechanical Engineering,
- Biomedical Engineering,
- Electrical Engineering, and
- Mathematics and Computer Science.
The challenging goal of the project is to design a hybrid neural/in-silico AI computer which leverages the computation of neural cultures hosted on a microfluidic Brain-on-Chip device to solve real-world AI problems. The hybrid AI computer will consist of an in-silico Bayesian control agent and a Brain-on-Chip device, which shall communicate via the common principle of Free Energy Minimization (FEM).
The announced PhD position focuses on the hard-ware development of
microfluidic Brain-on-Chip devices and
interfaces to in-silico control agents for the purpose of building a hybrid AI computer. For this position, a critical reflection on
biomaterials, electrically embedded microfluidic platforms, integrated multi electrode arrays, and
fast and high-quality data acquisition systems is required. The successful candidate will design innovative ways to create microfluidic platforms and will have a central role in building the hardware of the hybrid AI system. Furthermore, the techniques developed will be usable for
material and toxicity screening,
drug development and
individualized care and cure. The successful candidate will be hosted at the Department of Mechanical Engineering and co-supervised by Department of Biomedical Engineering.
Paired with the announced position is a second PhD position hosted at the Electrical Engineering department and co-supervised by the Department of Mathematics and Computer Science. The second PhD candidate will focus on the development of in-silico Bayesian control agents via probabilistic programming. The two PhD students will collaborate closely to achieve the final goal of developing a hybrid neural/in-silico AI computer. In particular, the two PhD students will work together on the development of interfaces between the in-silico Bayesian control agent and the Brain-on-Chip device.
The preferred starting date of this position is October 2021.