Research Associate/PhD Student: Learning-Based Relaible Mixed-Criticality System Design

13 Apr 2024
Job Information

Organisation/Company

Ruhr University Bochum

Research Field

Computer science » Computer architecture

Researcher Profile

Recognised Researcher (R2)
Established Researcher (R3)

Country

Germany

Application Deadline

29 Apr 2024 - 00:00 (UTC)

Type of Contract

To be defined

Job Status

Negotiable

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

The Chair of Embedded Systems at the Faculty of Electrical Engineering and Information Technology is looking for a research associate (m,f,x) for 3 years, 39,83 hours per week, TVL E13, to work on "Learning-Based Reliable Mixed-Criticality System Design" project.

Abstract:

A wide range of embedded systems found in many industrial application domains, such as automotive and avionics, are evolving into Mixed-Criticality (MC) systems, where various applications in terms of assurance levels are executed onto a common platform to meet cost, space, timing, and power consumption requirements while guaranteeing a safe operation. With the technology scaling in these modern embedded platforms, which leads to exacerbating the rate of manufacturing defects and physical fault rates, the safety and reliability issues have increased tremendously in all electronic systems, from unreliable execution of MC applications to unreliable hardware. To design a reliable system, fault mitigation and reliability methods need to be applied. This project investigates the feasibility of developing a hybrid Machine-Learning (ML)-based reliable design for these systems to estimate and improve reliability, QoS, and power consumption objectives.

The successful candidate (m,f,x) will:

• model, analyze, and explore reliability for embedded MC systems,
• investigate ML techniques and determine efficient ones for objective optimization,
• develop novel mechanisms to design reliable embedded MC systems,
• implementing proposed mechanisms on a target hardware platform,
• publish the works in international conferences and journals.

We aim at attracting the best talent in the respective research fields and expect the following:

• an outstanding university degree (Master’s degree or equivalent) in computer science and electrical engineering;
• strong architecture background with general purpose multi-core platforms;
• good knowledge of Computer Architecture and algorithm design;
• good understanding of machine learning
• proficiency in programming skills (C/C++ and Python);
• very good interpersonal and communication skills; in particular, the ability to - effectively work in collaborative research efforts;
• fluency in English – written and oral.

Requirements
Additional Information

Website for additional job details

https://www.hipeac.net/jobs/14629/research-associatephd-student-learning-based-…

Work Location(s)

Number of offers available

1

Company/Institute

Ruhr University Bochum

Country

Germany

City

Bochum

Geofield

Where to apply

Website

https://jobs.ruhr-uni-bochum.de/jobposting/f0b9adb3b69feb75fdf01d0848a682660341…

Contact

City

Bochum

Website

http://www.esit.rub.de/
https://twitter.com/ruhrunibochum

STATUS: EXPIRED