The Embedded Systems Research Unit (ES Unit) of the Information and Communication Technology Center of the Bruno Kessler Foundation (FBK-irst), Trento, Italy consists of about 25 people, including researchers, post-docs, PhD students, Master Students, and programmers. The Unit carries out basic and applied research, tool development and technology transfer in the field of automated planning for different applicative contexts, and in the field of design and verification of embedded systems.
Current research directions include:
- Predictive maintenance by combining model based reasoning with machine learning approaches;
- Formal Verification of complex embedded systems leveraging on model checking techniques;
- Formal Safety Analysis, based on the integration of traditional and symbolic techniques.
- Contract-based engineering and contract-based formal verification of aerospace systems using model checking techniques;
- Formal contract-based verification relying on model checking techniques;
- Formal Requirements Analysis based on temporal logic checks;
- Satisfiability Modulo Theory, and its application to planning and scheduling, verification of hardware, embedded critical software, and hybrid systems (Verilog, SystemC, C/C++, StateFlow/Simulink, SCADE);
- Model based planning and scheduling for robotic systems, for the management of autonomous vehicles, for drones to explore critical environment, factory automation, and for process optimizations (with applications in the field of Industry 4.0), leveraging model checking, satisfiability modulo theory, and combining explicit and symbolic search techniques;
- Model based on-board autonomy for different vehicles (AUV, ROV) using planning and scheduling techniques;
- Model based execution and monitoring of mission plans and assumptions under which the mission plan have been generated;
- Model based recovery relying on planning and scheduling techniques.
More information about the ES Unit is available at http://es.fbk.eu/.
The ES Unit has an opening for a PostDoc position in the field of predictive maintenance for industrial applications in the framework of several research and technology transfer projects. The successful candidate will be employed for a period of at least two years (with a trial period of 6 months). He/She will carry out research activities in the field of predictive maintenance applied to the analysis of complex critical designs. The candidate is expected to perform activities related to the following research topics:
- Development of techniques and tools for combining data driven and model based reasoning to learn models and/or to improve the quality of the models at the basis of the model based approach to run-time monitoring and predictive maintenance;
- Development of novel techniques for combining model based reasoning with machine learning to reduce the learning phase, and to improve the quality of the answer generated by the machine learning algorithms, with applications in predictive maintenance, reliability, availability, maintainability, safety and security of data;
- Development of a scalable and generic infrastructure for model based predictive maintenance that will allow for different form of analysis to combine sensor data to infer proper abstract states to drive then machine learning algorithms and/or statistical model checking algorithms in predicting the evolution of a system (e.g. future faults, remaining useful lifetime, …).
- Development of techniques and tools for the automated synthesis of run-time monitor for diagnosis and prognosis, and techniques and tools for model-based synthesis of drivers connecting application to sensors and enriching sensors with meta-data.
The candidate is expected to work in collaboration with other researchers, programmers, and students involved in the project. Moreover, the candidate is expected also to interact with industrial partners and to spend some time at industrial partner premises.
The ideal candidate should have:
- PhD in computer science, mathematics or electronic engineering (to be completed by mid 2019);
- Software development skills (preferably in C, C++, Python or Java);
- Ability to carry out an independent research program;
- Ability to work in a collaborative environment and deliver in research projects and possibly in industrial projects;
- Oral and written proficiency in English
In depth previous experience in at least one of the following areas:
- Predictive Maintenance
- Machine Learning
- Symbolic Model Checking
- Solid background in logic
- Temporal Logics and Property Specification Languages
- Satisfiability Modulo Theory
- Formal Specification and Analysis of Architectures
Type of contract: Fixed Term Contract (research profile CCPL)
Gross annual salary: about € 39.300
Working hours: full time
Start date: January 2019
End Date: December 2020
Workplace: Trento - Povo
Benefits: flexi-time, company subsidized cafeteria or meal vouchers, internal car park, welcome office support for visa formalities, accommodation, social security, etc., reductions on bank account opening fees, public transportation, sport, language course fees. More info at https://www.welfarefbk.info/
Candidates must submit their application by clicking "Apply online" at the bottom of this page. Please make sure to enclose the following documents with your application (pdf format):
- Detailed CV
- Cover Letter (explaining your motivation for this specific position)
- 3 professional references (e-mails and/or phone numbers)
Application deadline: 20th December 2018
Please read our Regulations on the recruitment and selection of fixed-term personnel (effective from October 15, 2018) before completing your application.
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