[Hol-info] Post-doc position in the field of Predictive Maintenance at Fondazione Bruno Kessler

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A RESEARCHER IN THE FIELD OF PREDICTIVE MAINTENANCE FOR THE EMBEDDED
SYSTEMS RESEARCH UNIT (ES)

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Job Description
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The Embedded Systems (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, â¦).
* 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.

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Job requirements
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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

Additional requirements:

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

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Employment
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Type of contract: Fixed Term Contract (research profile  CCPL)
Gross annual salary: about â¬ 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/

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Application
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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.

For further administrative information, please contact the Human
Resources Services at jo...@fb...

For technical inquiries about the position, send an e-mail at es...@fb...

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The Embedded System Unit (ES Unit)
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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/.