We are looking for motivated candidates interested in pursuing a PhD on Encoding and Sampling of Constrained Signal Spaces for Validation of Cyber-Physical Systems
This fully-funded thesis supervised by Nicolas Basset and Thao Dang will
take place in the Tempo team at the laboratory Verimag (Grenoble, France)
in the context of validation, monitoring and control of cyber-physical
systems modelled by timed and hybrid systems.
The thesis consists of theoretical development on:
– defining metrics for signals that satisfy temporal constraints expressed
with different formalisms: timed automata, signal temporal logic, timed
– parametrizing such constrained signal sets. Each parameter valuation maps
to a signal in the constrained sets, and such parametrizations enable random
sampling and optimization directly over constrained signal sets without
resorting to costly rejection sampling methods.
– learning a constrained signal set that best describes a finite set of signals.
This theoretical framework will then be applied to validation and control
of cyber-physical systems in particular from automotive industry.
The student should have (when the thesis begins) a Master degree in Computer
Science, Mathematics or Control Engineering, and a solid background in a
non-empty subset of Computer Science (algorithms, automata, logics), control
theory, optimization, formal methods and statistical reasoning.
Candidates who are ready to learn new things and complete their background,
are kindly requested to send e-mail (with “PhD-candidate” in the title)
a CV, a motivation letter, and a university transcript and Master manuscript
(if already available), to email@example.com and
Nicolas Basset and Thao Dang