Connectionists: University of Luxembourg: Research Associate (Postdoc) in Machine Learning and Software Engineering

[Fabrizio PASTORE]

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from PhD holders in the general areas of machine learning and software engineering within its SVV research group. For further information, you may refer to http://emea3.mrted.ly/2i5w2


	• Fixed-term contract 2 years (CDD), full-time 40 hrs/week
	• Number of positions: 1
	• Start day: Fall 2020, upon agreement
	• Ref: RCREQ0004458
	• Highly competitive salary


***Your Role

This is a fully funded position for 2 years within the research project "FUNTASY - Functional Safety for Autonomous Systems". A possible extension for one additional year is already covered by the project funding.

FUNTASY concerns the development of automated techniques to support functional safety practices in autonomous systems. Autonomous systems like self-driving cars have the potential to reshape our future by automating complex tasks and preventing human errors; unfortunately, their adoption in safety-critical contexts remains under debate. Indeed, being based on black-box machine learning solutions such as Deep Neural Networks, they cannot undergo traditional software safety certification processes that rely on the understandability of the system implementation. FUNTASY will overcome such limitations by providing automated solutions to (1) verify autonomous systems software, (2) generate explanations for software behaviour, (3) improve autonomous systems software. Enabling solutions will be simulation technology, evolutionary algorithms, and methods to capture and explain the internal DNN behaviour. FUNTASY will be a collaboration between the University of Luxembourg’s SnT Centre and IEE – an international sensing systems supplier based in Luxembourg (www.iee.lu). The project research directions include, but are not limited to, the automated generation of inputs to verify DNN-based components, the interpretation and explanation of DNNs, the identification of strategies to retrain DNNs efficiently, the improvement of DNN robustness, adversarial testing.

The successful candidate will work with Dr. Fabrizio Pastore, Chief Scientist II at SnT, industrial supervisors from IEE, and will join the SVV research group, headed by Prof. Lionel Briand. SVV focuses on the development and design of reliable, safe, and secure software systems, carrying out both upstream activities such as requirements quality assurance and architecture analysis, as well as downstream verification & validation activities, primarily software testing and analysis. For further information, you may refer to https://wwwfr.uni.lu/snt/research/software_verification_and_validation_lab

The position holder will be required to perform the following tasks:

	- Contribute to the project “FUNTASY - Functional Safety for Autonomous Systems”
	- Carry out research in the predefined areas
	- Disseminate results through scientific publications
	- Present results in well-known international conferences and workshops
	- Coordinate research activities and deliver outputs
	- Implement solutions
	- Provide guidance to PhD and MSc students
	- Organize relevant workshops and demonstrations

***Your Profile

Qualification: The candidate should possess a PhD degree in Computer Science, Machine Learning, or Software Engineering.

Experience: The ideal candidate should have some knowledge and experience in a number of the following topics:



***We offer

The University offers a two-year employment contract and may be extended up to five years. The University offers highly competitive salaries and is an equal opportunity employer. You will work in an exciting international environment and will have the opportunity to participate in the development of a newly created university.

***Further Information

Applications, written in English, should be submitted ONLINE and should include:

	- Curriculum Vitae (including your contact address and work experience, list of publications)
	- Cover letter indicating the research area of interest and your motivation
	- A research statement (max 1 page)
	- Contact information for 3 referees
	- Early submission is encouraged, applications will be processed upon arrival.

***Further information

For further information, go to  http://emea3.mrted.ly/2i5w2 or contact fabrizio.pastore at uni.lu

Please apply ONLINE formally through http://emea3.mrted.ly/2i5w2. Applications by email will not be considered.