The Eindhoven Artificial Intelligence Systems Institute (EAISI) is funding 2 PhD positions for the highly innovative BayesBrain project, in collaboration with the departments of

• Electrical Engineering,   
• Mathematics and Computer Science,
• Mechanical Engineering, and
• Biomedical Engineering.

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 development of in-silico Bayesian control agents and autonomous systems that learn purposeful behavior through interactions with their environment. In particular, the project will be based on the paradigms of probabilistic programming, Bayesian inference, and biologically plausible message passing algorithms on factor graphs (http://forneylab.org). The successful candidate will be hosted at BIASlab (http://biaslab.org) at the Department of Electrical Engineering and be co-supervised by the Department of Mathematics and Computer Science.

Paired with the announced position is a second PhD position hosted at the Mechanical Engineering department and co-supervised by the Department of Biomedical Engineering. The second PhD candidate will focus on the development of Brain-on-Chip devices. 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.

• Master's degree in computer science, electrical engineering, mathematics, physics or a related discipline, with excellent grades
• Strong background in Bayesian inference, probabilistic machine learning, or probabilistic programming
• Excellent coding skills (Julia, Python, C++)
• Ability and aspiration to work in a multi-disciplinary team, combining material science, neuroscience, and probabilistic machine learning
• Excellent command of written and spoken English

• A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
• A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
• To develop your teaching skills, you will spend 10% of your employment on teaching tasks.
• To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program).
• A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
• Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
• Should you come from abroad and comply with certain conditions, you can make use of the so-called '30% facility', which permits you not to pay tax on 30% of your salary.
• A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
• Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.