KEYWORDS: Evolutionary Computation; Neuroevolution; Evolvable Hardware; Lifelong Learning; Continuous Adaptation.
DESCRIPTION: In the Centre of Industrial Electronics (CEI) at Universidad Politécnica de Madrid (UPM), we are looking for a highly motivated and talented PhD student in the field of Evolvable and Neuroevolvable Hardware for Cyber-Physical Systems (CPS). The proposed PhD research project is focused on the following topics:
- Neuroevolutionary algorithms for lifelong learning in robust Cyber-physical systems.
- Evolutionary algorithms for automatic feature extraction for Self-adaptive CPSs.
- Hardware architectures for Evolvable and Neuroevolvable systems in reconfigurable FPGAs.
- Robust control techniques for autonomous CPSs based on automatic learning and evolvable hardware.
- Fault-tolerance in Cyber-Physical Systems based on evolvable and neuroevolvable hardware properties.
The PhD candidate will be part of a highly international and enthusiastic team. This 3-year position will be funded within the H2020 KYKLOS 4.0 (An Advanced Circular and Agile Manufacturing Ecosystem based on the rapid reconfigurable manufacturing process and individualized consumer preferences) project (https://cordis.europa.eu/project/id/872570).
The three-year PhD grant includes health insurance coverage and a gross salary of 18,200 € in 12 monthly pays. Expenses for attending conferences, summer schools, and workshops are also covered with the available funding.
BASIC QUALIFICATIONS: Master’s degree in Electrical / Electronics / Computer Engineering, Computer Science, Physics; or similar. Previous research activities in the fields of interest will be highly appreciated.
PREFERRED SKILLS: Very good knowledge of digital hardware design and VHDL; High-level synthesis tools for FPGAs; Design of mixed software/hardware systems; Experience with Machine Learning and Evolutionary Algorithms is also valuable. A high level of English, as well as being willing to learn Spanish, are also necessary for this position.
POSITION AVAILABLE: The selection procedure will open in October 2020 and will be maintained opened until the position is covered. The starting date is flexible, but preferred ASAP.
INFORMATION: If you are interested in this position and want to have more details about it, please contact Dr. Andrés Otero (email@example.com) or Dr. Jorge Portilla (firstname.lastname@example.org), including the reference PhD_ML_RC. For the formal application, the following documents will be required:
- Academic transcript of courses followed and grades obtained provided by your institution.
- Brief letter describing your motivation and previous experience.
- Any reference you can provide from professors of the field.