Developing theory of Reservoir computing for sensing applications

Information about the project
The project aims to develop thorough theoretical understanding of the possibilities related to using reservoir computing for advanced sensing applications. The idea to use reservoir computing for sensing is entirely novel. If proven successful it will have enormous technological implications  in various fields of bio-sensing or bioengineering. Reservoir computing is a paradigm of unconventional computation. A reservoir is a dynamical system with sufficienlty complex dynamics. Under well-defined conditions such systems can process information without prior training, i.e. they can be easily prepared in any desired information processing mode for advanced computations like pattern recognition or classification.  

Major responsibilities
The work will be done in a close collaboration with several experimental groups that are working on an experimental prototype in the context of ion concentration characterization, and will consist of two major parts (a) the fundamental theoretical research, and (b) applied theoretical research.

(a) The fundamental theoretical development aiming at in depth theoretical investigation of the feasibility of the reservoir based sensing concept:
(a1) Develop generic sensing model of computation.
(a2) Generalize the model to the ion-concentration sensing context.
(a3) Develop a theoretical model of the sensing-reservoir dynamics in the context of ion-concentration sensing with the following components: memristor networks, organic transistors, lipid flow memristors, photoactive elements, or silicon nanowires.

(b) Dissemination of the theoretical results to, and the use of the experimental results from the experimental groups:
(b1) Develop necessary simulation tools in close synergy with experimental groups: software development, experimental data analysis, model parameterization using the experimental data.
(b2) Provide guidelines for the experimental activities regarding the device design (to improve sensing capacity).
(b3) Suggest suitable sensing scenarios.

Position summary
Full-time temporary employment. The position is limited to a maximum of four years.

Qualifications
To qualify as a PhD student, you must have a master's level degree corresponding to at least 240 higher education credits in the field of theoretical physics, or theoretical computer science, or other (strongly) related areas.

A suitable candidate should have a good operational knowledge on the following topics: complex dynamical systems, non-equilibrium statistical physics (equilibrium versus non-equilibrium, transients, stable vs unstable states Markov processes, the master equation and master equation simulation techniques; e.g. the minimal process method or other variants, experience in algorithmic development of simulation techniques). Bonus is an operational knowledge on the following topics of theoretical computer science: models of computation, computability theory, Turing universality/completeness. Good understanding of the measure theory, point set topology, approximation theorems, Banach spaces, and measure theory is advantageous. An experience in unconventional information processing paradigms such as neuromorphic computing or reaction-diffusion computing is a strong bonus. In general the successful candidate should have good problem solving skills, and good analytic and programming skills.

Chalmers continuously strives to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.

Application procedure
The application should be marked with Ref 20150170 and written in English. The application should be sent electronically via Chalmers webpage.


Application deadline: May 31, 2015

Important note: Interview invitations will be sent by June 3, and interviews will be conducted very soon after that, during the second week of June (June 8th – June 12th). Please make sure to plan accordingly.

For questions, please contact:
Zoran Konkoli, MC2, zorank@chalmers.se, +46 31 7725480

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. *** 
   



Chalmers University of Technology conducts research and education in engineering sciences, architecture, technology-related mathematical sciences, natural and nautical sciences, working in close collaboration with industry and society. The strategy for scientific excellence focuses on our eight Areas of Advance; Built Environment, Energy, Information & Communication Technology, Life Science, Materials Science, Nanoscience & Nanotechnology, Production and Transport. The aim is to make an active contribution to a sustainable future using the basic sciences as a foundation and innovation and entrepreneurship as the central driving forces. Chalmers has around 11,000 students and 3,000 employees. New knowledge and improved technology have characterised Chalmers since its foundation in 1829, completely in accordance with the will of William Chalmers and his motto: Avancez!