Your job alert was successfully created.
KU Leuven
15 PhD positions in the EU Horizon 2020 Marie Skłodowska-Curie Project: Safer Autonomous Systems
KU Leuven
KU Leuven is an autonomous university. It was founded in 1425. It was born of and has grown within the Catholic tradition.
Visit employer page
JOB DETAILS
Published: 21 days ago
Application deadline: Aug 31
Location: Leuven, Belgium
See application details in the description
SHARE THIS JOB

15 PhD positions in the EU Horizon 2020 Marie Skłodowska-Curie Project: Safer Autonomous Systems

Applications are invited for 15 PhD positions (“Early Stage Researchers”) to be funded by the Marie-Sklodowska-Curie Innovative Training Network “SAS – Safer Autonomous Systems” within the Horizon 2020 Programme of the European Commission. SAS is a consortium of high profile universities, research institutions and companies located in Belgium, UK, France, Germany, The Netherlands, Norway and Ireland (Figure 1). This gives SAS some of the best and most relevant of European industry and the key academic players, guaranteeing not only an exciting interdisciplinary, intersectoral research-and-training programme, but also a head-start for bringing about trust in autonomous systems. Each of the 15 ESRs will be working towards a PhD degree, supported by a carefully chosen supervisory team that maximizes both scientific excellence as well as interdisciplinary and intersectoral collaboration. The 15 SAS ESRs will not only receive state-of-the-art science/technology training but will also benefit from a unique soft-skills training programme. This will kick-start their careers as highly employable professionals tackling challenges across many industrial sectors comprising, but not limited to, automotive, robotics, nautical, manufacturing, aeronautics, agriculture and medical industry.

Key dates:

  • June 29 2018: Launch of 15 ESR Positions
  • August 31 2018: Deadline for on-line application
  • September 24 2018: Circulation list “preselected candidates”
  • November 27 2018: SAS Recruitment Event
  • November 28 2018: Circulation list “recruited SAS ESRs”
  • January 1 2019: Targeted starting date for ESR contracts

Key background info

Number of positions available 15 PhD Positions

Research Fields Software Engineering - Electronic Engineering - Safety Engineering – Computer Science – System Engineering - Machine Learning – Artificial Intelligence – Robotics – ICT Law

Keywords Functional Safety – Safety Assurance - Dependability – Trustworthy Systems - Autonomous Systems – Self-Driving Vehicles – Autonomous Vessels – Clinical Robots – Pilotless Planes – Autonomous Agricultural Robots - Model-Based Analysis – HighIntegrity Systems - Liability

Career Stage Early Stage Researcher (ESR) or 0-4 yrs (Post Graduate)

Benefits and salary The successful candidates will receive an attractive salary in accordance with the MSCA regulations for Early Stage Researchers. The exact (net) salary will be confirmed upon appointment and is dependent on local tax regulations and on the country correction factor (to allow for the difference in cost of living in different EU Member States). The salary includes a living allowance, a mobility allowance and a family allowance (if married). The guaranteed PhD funding is for 36 months (i.e. EC funding, additional funding is possible, depending on the local Supervisor, and in accordance with the regular PhD time in the country of origin). In addition to their individual scientific projects, all fellows will benefit from further continuing education, which includes internships and secondments, a variety of training modules as well as transferable skills courses and active participation in workshops and conferences.

On-line Recruitment Procedure (see Appendix 1 for full description)
All applications proceed through the on-line recruitment portal on the www.etn-sas.eu website. Candidates apply electronically for one to maximum three positions and indicate their preference. Candidates provide all requested information including a detailed CV (Europass format obligatory) and motivation letter. During the registration, applicants will need to prove that they are eligible (cf. ESR definition, mobility criteria, and English language proficiency). The deadline for the on-line registration is August 31 2018. The SAS Recruitment Committee selects between 20 and maximum 30 candidates for the 15 Phd Positions for EU MSCA-ETN SAS (2018) 2 Recruitment Event which will take place in Bruges (Belgium) (November 27 2018). The selected candidates provide a 20-minute presentation and are interviewed by the Recruitment Committee. Candidates will be given a domain-relevant peer-reviewed paper (prior to the recruitment event) by their prioritised Supervisor and will be asked questions about this paper during the interview to check if the candidate has the right background/profile for the ESR position. Prior to the recruitment event, skype interviews between the Supervisors and the candidates are recommended, along with online personality tests. In order to facilitate their travel, selected candidates (from outside Belgium) receive a fixed, lump sum of 250 euro (paid by the prioritised Supervisor). In order to avoid delays in reimbursements, candidates are asked to keep all invoices and tickets (cf. train, plane, hotel...). The final decision on who to recruit is communicated the day after the Recruitment Event (November 28 2018). The selected ESRs are to start their research as quickly as possible (target: January 1 2019).

Applicants need to fully respect three eligibility criteria (to demonstrated in the Europass cv):
Early-stage researchers (ESR) are those who are, at the time of recruitment by the host, in the first four years (full-time equivalent) of their research careers. This is measured from the date when they obtained the degree which formally entitles them to embark on a doctorate, either in the country in which the degree was obtained or in the country in which the research training is provided, irrespective of whether or not a doctorate was envisaged.

Conditions of international mobility of researchers:
Researchers are required to undertake trans-national mobility (i.e. move from one country to another) when taking up the appointment. At the time of selection by the host organisation, researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of their host organisation for more than 12 months in the 3 years immediately prior to their recruitment. Short stays, such as holidays, are not taken into account.

English language: Network fellows (ESRs) must demonstrate that their ability to understand and express themselves in both written and spoken English is sufficiently high for them to derive the full benefit from the network training.

The 15 available PhD positions

(see Figure 2 for interactions between ESRs/WPs)

ESR1: Development of a generic framework to monitor and handle safety of autonomous systems at run-time
Host:
LAAS-CNRS (France)
Main supervisor: Prof. J. Guiochet (jeremie.guiochet@laas.fr)
Co-supervisors/mentors: Prof. M. Trapp (Fraunhofer – Germany), Dr. P. Barber (Jaguar Land Rover – UK)
Duration: 36 months
Required profile: Computer Science, Software Engineering
Desirable skills/interests:
Embedded Systems, Dependability
Objectives: ESR1 will define, implement and validate a framework facilitating black/grey-box monitoring of autonomous functionality at run-time. ESR1 will combine and extend existing approaches for run-time error detection and handling for assuring safety of autonomous systems without the need to prove the correctness / safety of the monitored (Artificial Intelligence) algorithms as such.

ESR2: Development of an adaptive platform for resilient autonomous systems based on a MAPE-K cycle
Host:
Fraunhofer (Germany)
Main supervisor: Prof. M. Trapp (mario.trapp@iese.fraunhofer.de)
Co-supervisors/mentors: Prof. J.C. Fabre (LAAS-CNRS – France), Dr. S. Burton (Bosch – Germany)
Duration: 36 months
Required profile: Software Engineering
Desirable skills/interests: Embedded Systems, Dependability, Self-Adaptation
Objectives:
ESR2 will integrate adaptive functionality and faulttolerance into a safe, fail-operational run-time adaptation platform for resilient autonomous systems and evaluate this in an industrial case study.

ESR3: Dynamic safety handling of autonomous systems-ofsystems with run-time safety contracts
Host:
Fraunhofer (Germany)
Main supervisor: Prof. M. Trapp (mario.trapp@iese.fraunhofer.de)
Co-supervisors/mentors: Prof. T. Kelly (Univ. of York - UK), Dr. S. Burton (Bosch – Germany)
Duration: 36 months
Required profile: Software Engineering
Desirable skills/interests: Embedded Systems, Safety
Objectives: ESR3 will extend the current state-of-the-arte dynamic safety contracts facilitating a more systematic, yet more modular and flexible, dynamic safety assurance of autonomous systems, and evaluated this in an industrial case study.

ESR4: Creating Software Design Guidelines and Testing Specifications for Non-Functional Requirements in Safetycritical Autonomous Systems Host: KU Leuven (Belgium)
Main supervisor: Prof. J. Boydens (Jeroen.boydens@kuleuven.be)
Co-supervisors/mentors: Prof. E. Steegmans (KU Leuven - Belgium), Dr. P. Munk (Bosch – Germany)
Duration: 36 months
Required profile: Software Engineering, Software Verification and Validation
Desirable skills/interests:
Functional Safety Engineering, Pattern Oriented Software Approach, Machine Learning
Objectives: ESR4 will develop innovative software design and testing guidelines, related to non-functional requirements. In addition, ESR4 will evaluate the developed strategies within industry-relevant safety-critical applications.

ESR5: Making Connectivity Work Reliably in a diverse Range of Environments
Host:
KU Leuven (Belgium) Main supervisor: Prof. D. Pissoort (davy.pissoort@kuleuven.be)
Co-supervisors/mentors: Prof. G. Vandenbosh (KU Leuven - Belgium), Eng. J.K. van der Ven (RH Marine – The Netherlands)
Duration: 36 months
Required profile: Electronic Engineering
Desirable skills/interests: Electromagnetism, Telecommunication, Functional Safety, Reliability
Objectives: ESR5 will compare the effectiveness of different types of diverse redundancy (inversion, spatial, frequency, time, etc.) and 15 Phd Positions for EU MSCA-ETN SAS (2018) 3 the robustness of different wireless communication protocols for different types of EMI, ageing, thermal stress, etc.

ESR6: Virtual worlds generation for testing autonomous robots in simulation
Host:
LAAS-CNRS (France) Main supervisor: Dr. H. Waeselynck (Helene.waeselynck@laas.fr)
Co-supervisors/mentors:
Dr. R. Alexander (Univ. of York - UK), Dr. M. Albert (Sick – Germany)
Duration: 36 months
Required profile: Computer Science, Software Engineering
Desirable skills/interests: Robotics, Simulation, Software Validation
Objectives: ESR6 will develop a complete and generic framework allowing simulation-based testing of an autonomous robot in virtual worlds. The automated world generation process will be guided by test objectives and analysis of previous test runs.

ESR7: Rigorous Design and Evaluation of Situation Coverage Testing for Autonomous Vehicles
Host:
University of York (UK)
Main supervisor: Dr. R. Alexander (rob.alexander@york.ac.uk)
Co-supervisors/mentors: Dr. H. Waeselynck (LAAS-CNRS - France), Dr. D. Ward (Horiba-Mira – UK)
Duration: 36 months
Required profile: Software Engineering
Desirable skills/interests: Robotics Simulation
Objectives: ESR7 will create and empirically evaluate a testing method and prototype tools for simulated-situation testing of autonomous cars in an urban road environment.

ESR8: Model-based System Analysis Techniques to determine propagation paths of functional insufficiencies in softwareintensive systems
Host:
Bosch (Germany) Main supervisor: Dr. P. Munk (peter.munk@de.bosch.com)
Co-supervisors/mentors: Prof. J. Boydens (KU Leuven - Belgium), Prof. P. Liggesmeyer (TU Kaiserlautern – Germany)
Duration: 36 months
Required profile: Software of Systems Engineering
Desirable skills/interests: Automotive, Safety, Model-Based Engineering
Objectives:
ESR8 will investigate the application of model-based system analysis techniques for functional insufficiencies, including probabilistic ways to model the uncertainties and the completeness of such an analysis.

ESR9: Model-based System Analysis of the Robustness of Autonomous Systems against ElectroMagnetic Interference
Host:
KU Leuven (Belgium)
Main supervisor: Prof. D. Pissoort (davy.pissoort@kuleuven.be)
Co-supervisors/mentors: Prof. G. Vandenbosch (KU Leuven - Belgium), Dr. A. Ruddle (Horiba-Mira – UK)
Duration: 36 months
Required profile: Electronic Engineering or Systems Engineering
Desirable skills/interests: Model-Based Engineering, Electromagnetic Simulations, Behavioural Modelling
Objectives: ESR9 will integrate behavioural system models within a highly-efficient, statistical framework for electromagnetic simulations and validate the resulting virtual V&V methodology on an industrial test-case.

ESR10: From static assurance cases at design-time to executable assurance cases at run-time
Host:
University of York (UK)
Main supervisor: Prof. T. Kelly (tim.kelly@york.ac.uk)
Co-supervisors/mentors: Prof. J. Guiochet (LAAS-CNRS - France), Dr. E. Landre (Equinor – Norway)
Duration:
36 months
Required profile: Software Engineering
Desirable skills/interests: Safety-Critical / High Integrity Systems, Programming Languages
Objectives: ESR10 will establish an executable model of structured argumentation (based UoY’s previous work on the OMG Structured Assurance Case Meta-model) in which the safety case (and these patterns) consists of an executable set of rules (claims, truths) to be sustained and maintained at run-time, with options and criteria to be resolved as the system configuration and environment evolve. ESR10 will evaluate the safety executive in a series of challenging scenarios for two different given application contexts.

ESR11: Assurance case structures for machine learning in the decision making of highly autonomous systems
Host:
University of York (UK)
Main supervisor: Prof. T. Kelly (tim.kelly@york.ac.uk)
Co-supervisors/mentors: Dr. R. Alexander (Univ. of York - UK), Dr. S. Burton (Bosch – Germany)
Duration: 36 months
Required profile:
Software Engineering
Desirable skills/interests: Artificial Intelligence (in particular Machine Learning), Safety-Critical / High Integrity Systems
Objectives: ESR11 will rigorously establish and evaluate assurance case structures (expressed as GSN – Goal Structuring Notation – and SACM – Structured Assurance Case patterns) for the assurance of machine learning in safety-critical applications. ESR11 will evaluate the application of the assurance case patterns in a number of autonomous driving applications and scenarios.

ESR12: Assuring autonomous sailing from A to B while minimizing operational costs
Host:
RH Marine (The Netherlands) Main supervisor: Eng. J.K. Van der Ven (Jan-Kees.vanderVen@rhmarine.com)
Co-supervisors/mentors: Prof. T. Kelly (Univ. of York - UK), Prof. J. Boydens (KU Leuven – Belgium)
Duration:
36 months
Required profile: Marine engineering or control engineering
Desirable skills/interests: Artificial Intelligence, Optimization, Vessel Motion Control, Data Fusion, Sensor Fusion
Objectives: The ESR will enable safe autonomous sailing from A to B while minimizing operational costs, by performing the following steps: optimization algorithm, situational awareness algorithm and collision/grounding avoidance algorithm. The optimization algorithm will obtain a to be sailed track by a vessel (or a fleet of vessels) from A to B, optimized in relation to financial objectives taking into account real-life constraints. Next to this optimization algorithm the ESR will develop a situational awareness algorithm, combining the input of several types of sensors in order to create a situational awareness output to a to be developed collision/grounding avoidance algorithm. The ESR will integrate the optimization algorithm, collision avoidance algorithm and current motion control systems of vessels in order to simulate a number of scenario’s fulfilling the defined objectives.

ESR13: Safety assurance for Clinical Conversational Bots
Host:
University of York (UK)
Main supervisor: Dr. I. Habli (Ibrahim.habli@york.ac.uk)
Co-supervisors/mentors: Prof. J. Guiochet (LAAS-CNRS - France), Eng. E. O’Caroll (Portable Medical Technology – Ireland)
Duration: 36 months
Required profile: Software Engineering
Desirable skills/interests: Artificial Intelligence, Machine Learning, Healthcare
Objectives: ESR13 will create a systematic understanding of the safety challenges associated with the use of intelligent conversational bots. The ESR will develop a safety concept and architectural strategies for clinical conversational bots, considering the intended clinical use, core technologies (natural language processing, clinical knowledge representation, automated reasoning and machine learning), medical conditions and patient variations and preferences.

ESR14: Dependability Assurance for Vehicle Autonomy
Host:
Horiba Mira (UK)
Main supervisor: Dr. A. Ruddle (alastair.ruddle@horiba-mira.com)
Co-supervisors/mentors: Prof. T. Kelly (Univ. of York - UK), Prof. D. Pissoort (KU Leuven – Belgium)
Duration: 36 months
Required profile: Electronic Engineering or Systems Engineering
Desirable skills/interests: Functional Safety, Cyber Security, Automation, Artificial Intelligence
Objectives: ESR14 will develop a unified and holistic approach to developing a range of assurance cases that could address a range of aspects of dependability for highly automated and fully autonomous vehicles

ESR15: Between Safety and Liability: Towards a Liability Allocation Framework for Safe Autonomous Systems
Host:
KU Leuven (Begium)
Main supervisor: Prof. P. Valcke (peggy.valcke@kuleuven.be)
Co-supervisors/mentors: Prof. D. Pissoort (KU Leuven - Belgium), Eng. A. Taillard (Airbus - France)
Duration: 36 months
Required profile: Master’s degree in law with sufficient coverage of EU and international law
Desirable skills/interests: Specialisation or equivalent experience in legal aspects of new technologies, preferably in a civil law jurisdiction
Objectives: ESR15 will identify legal criteria accommodating continuous adaptation while preserving conservative safety goals. The ESR will explore different models for liability allocation in various domains where highly autonomous systems could be implemented. The ESR will analyse and assess the aptness of existing legal frameworks for allocation of liability, such as the contractual liability, product liability etc., towards the development of a framework for allocation of liability in complex ecosystems reconciling distributed and shared control with stringent safety rules. Such a framework will serve as risk regulation tool improving legal certainty and ensuring a fair apportionment of risks, high level of safety and fair compensation.

ETN SAS project abstract and key project information

Autonomous systems offer humankind tremendous opportunities, like freeing us from mundane tasks, carrying out risky procedures and generally giving us more time to enjoy the things we like doing. However, we lack trust in many forms of autonomous systems: partly this is human nature, but primarily because these systems, such as self-driving cars, have not demonstrated their safety credentials. Only by making these systems safer can we expect their widespread acceptance. The Safer Autonomous Systems (SAS) ETN is about getting people to trust these systems by making the systems safer. In order to achieve this objective and to train a group of highly skilled, responsible, future innovators, we will bring together 15 early-stage researchers (ESRs) to investigate new forms of system-safety engineering, dependability engineering, fault-tolerant and failsafe hardware/software design, model-based safety analysis, safety-assurance case development, cybersecurity, as well as legal and ethical aspects. SAS will actively research the development of safer autonomous systems at multinationals like Bosch, but it also wants to stimulate the development of new safety designs, modelling and assurance techniques by involving the ESRs in SMEs and, potentially, their own start-ups. To help the ESRs put what they have learned during their research and S/T training into practice in their future careers, they will also receive soft-skills training to help them communicate effectively at all levels and become sought-after recruits. SAS is closely aligned with the high-priority areas of the EU, addressing many Horizon 2020 thematics, e.g., Industrial Leadership (Advanced manufacturing and processing), Societal Challenges (Smart, green and integrated transport; Secure, clean and efficient energy) and Excellent Science. But the most important output of SAS will be 15 well qualified people who have been trained to tackle many of the problems now being faced by European industry.

The SAS project is based on 6 Work Packages (WPs), three of which are S&T WPs (WP1–3), one for training (WP4), one for Exploitation, Dissemination and Communication (WP5) and one for Management (WP6). The S&T WPs are organized along 3 research tracks covering the 3 main steps in the safety-assurance process: (i) building safety and dynamic risk mitigation into the system by design, (ii) gathering evidence that the behaviour of the system will actually be safe, and (iii) combining these into a clear strategy that allows us to put our trust in the system.

WP1: Designing inherently safe autonomous systems
WP1 involves 5 ESRs and tackles the actual safety-aware design, i.e., making safety inherently part of the design process, of resilient autonomous systems, with 3 ESRs focusing on generic frameworks and methodologies to guarantee by-design safe behaviour during run-time and 2 ESRs focusing on specific hardware and software techniques-and-measures to achieve fault-tolerant – or even failoperational – behaviour.

ESR1 and ESR2 take up the challenge of developing generic frameworks to monitor and handle the safety of autonomous systems during run-time. No complex system can be considered fault-free and this is particularly true for autonomous systems having non-deterministic decision-making capabilities. The role of such a safety monitoring-and-handling framework is to observe the system and its environment and to trigger interventions that maintain the system’s safety, so-called safety rules. As for non-autonomous systems, a human operator takes a significant role in this faultmonitoring and, definitely, in the fault-handling, only a limited set of safety rules had to be considered in the past. In contrast, versatile autonomous systems will have to deal with a much richer set of safety rules. Moreover, these safety rules have to take into account the wide application of machine learning in autonomous systems, causing them to evolve over time, and the a-priori largely unknown open-context in which autonomous systems will be applied. Current fault-monitoring and fault-tolerance mechanisms, which are fixed prior to run-time, will no longer be sufficient. Dynamic adaptation of fault-detection and fault-handling will be a key ability for safe autonomous systems. ESR1 and ESR2 will be working on related, but complementary projects, with ESR1 having the task to extend current safety-monitoring frameworks such that they cover the whole chain from safety-constraint definition to the actual autonomous reactions to avoid a possible hazard, while ESR2 starts from a MAPE-K cycle (i.e., Monitoring, Analyse, Plan and Execute based on Knowledge represented in run-time models) to enable real-time adaptations of functionality, structure, and fault-tolerance mechanisms in order to assure the run-time resilience of autonomous systems.

ESR3 will run in parallel with ESR1 and ESR2 and go one step further and integrate dynamic safety handling of autonomous systems-of-systems through run-time safety contracts into the adaptive safety monitoring and handling framework. Driven by trends like ubiquitous computing and cyber-physical systems, new application domains for autonomous systems-of-systems have emerged. Cooperative agricultural vehicles such as harvesters and tractors that are combined into autonomous harvesting fleets to optimize harvesting in the field, car-to-car interactions that help to prevent accidents at intersections or optimize cruising speed, or plug-and-play emergency rooms supporting the rapid, on-demand (re-)configuration of surgical equipment are only a few promising examples. In such systems-of-systems, different devices are combined during run-time to fulfil higher-level emergent functionalities in a collaboration that cannot be provided by one of the involved systems on its own. Of course, the safety of such an autonomous system-of-systems must be guaranteed. However, classic safety assurance relies heavily on a complete understanding of the structure and behaviour, which is not available at design-time for an autonomous system-of-systems. It is therefore more reasonable to use the idea safety contracts between the different subsystems. Safety contracts are an effective way to conditionally describe the safety guarantees that a component should fulfil in order to make sure that the overall system-of-systems remains safe. Up until now, the use of safety contracts has mainly been limited to static, non-evolving systems. ESR3 will extend this approach to dynamic, modular safety contracts. In addition, these safety contracts will be a key element in the run-time safety-assurance strategies of ESRs 10 and 11 (WP3), covering two flavours of executable assurance.

ESRs 4 and 5 will work on effective techniques and measures that assure by-design that even under fault conditions the autonomous system remains safe without any human intervention. When autonomy increases, so does the software complexity and thus the likelihood that it contains faults. Therefore, ESR4 focuses on software design guidelines and testing specifications for nonfunctional requirements in safety-critical autonomous systems. Future applications of autonomous systems will rely heavily on different communication technologies to connect and interact with other devices, infrastructure, the “cloud”, etc. Although adding connectivity has its benefits, it also adds challenges, among which are most definitely its robustness and resilience. ESR5 focuses on more hardware-oriented design and testing specifications, which 15 Phd Positions for EU MSCA-ETN SAS (2018) 7 make connectivity work reliably under a diverse range of environments. This takes into account a combination of stresses, including electromagnetic interference, temperature and vibrations, aging, etc.

WP2: Providing evidence for autonomous systems
WP2 targets novel methodologies that allow us to evaluate, validate and verify the safety-aware design (WP1), meaning that safety can be guaranteed given the complex environment and extremely varied use-case scenarios that autonomous systems will be subjected to. This challenge cannot be underestimated. Just recently, Michael Bolle, President of Bosch, Corporate Research said in a speech: “We have looked at what it takes to physically validate autonomous driving, and the time needed was estimated at 100,000 years. We need breakthrough solutions from the research community.” As physical testing is too costly and too time consuming, we must turn to virtual, i.e., simulation- and model-based, testing.

ESRs 6 and 7 will collaborate to achieve a breakthrough with respect to the overall coverage of the model-based safety analysis. ESR6 will address the issue of the virtual-worlds generation and will apply this to autonomous robots. In other words, ESR6 answers the question “which operational situations and environments should be tested in the virtual world?” and starts from a criticality analysis. Once the most critical virtual worlds have been generated, ESR7 will evaluate and maximize the situation coverage of each of the virtual worlds. Exploiting combinatorial testing techniques, ESR 7 will determine exactly which simulation runs should be performed to maximally challenge robot's ability to cope with the features of its environment.

Whereas a classic model-based safety analysis often limits itself to failures of one or multiple components, the open-context nature of autonomous systems forces us to also consider the safetyapplications of functional insufficiencies. A typical example being a camera in a self-driving car that should prevent a collision with a human being, but only detects a human correctly in 99.9% of the cases. Therefore, ESR8 is going to look at model-based systemanalysis techniques to determine propagation paths of functional insufficiencies in software-intensive systems and will use probabilistic ways to model the uncertainties.

Complementary to ESR5 (WP1), ESR9 will also take up the challenge of the strong reliance of autonomous systems on wireless communication and will perform a model-based system analysis of the robustness of autonomous systems against electromagnetic interference. Combining efficient statistical electromagnetic modelling with behavioural modelling, the resulting behaviour of an autonomous system upon electromagnetic disturbances will be forecasted and evaluated.

WP3: Providing assurance strategies
The S&T WPs conclude with WP3, which pilots novel safetyassurance strategies, combining the previous 2 research WPs, thereby allowing us to put trust in the safe behaviour of autonomous systems. In total this WP involves 6 ESRs and, besides safety, also covers other design constraints such as security, reliability, availability and liability.

ESRs 10 and 11 both focus on dedicated assurance cases for autonomous systems. Existing standards, processes and practices place a great emphasis on how safety can be certified throughout the design and development stages. However, there is little guidance on how safety assurance should be maintained throughout the system’s operational life. Many assumptions about the environment and the system performance and use, particularly for complex and novel autonomous systems, that are made during the design and development stages might turn out to be incorrect during operation. From a safety point of view, this can threaten the validity of the safety case and weaken confidence in the actual safety of the system. Within SAS, two complementary approaches will be pursued to tackle this. On the one hand, ESR10 aims at making the transition from static assurance cases during design-time to executable assurance cases during run-time. Here, a safetyassurance case is structured argumentation, supported by evidence (WP2), intended to justify that the system is designed (WP1) such that its behaviour is acceptably safe when being put into service. While for non-autonomous systems, the whole safety case is traditionally developed, documented and accepted prior to operation, the safety case for some autonomous systems may instead need to be posed with residual obligations that are only satisfied during run-time. For example, the vast number of possible inter-vehicle and infrastructure configurations that an autonomous vehicle may encounter may require run-time verification of safety properties (such as end-to-end response times, or the integrity of received data) to sustain the safety case.Therefore, ESR10 will establish a new way of working with an executable set of claims that will be sustained and maintained during run-time. On the other hand, ESR11 will study assurance-case structures for machine learning in the decision making of highly autonomous systems. Currently, the use of machine learning or any other artificial intelligence technique, is not recommended for safety-critical tasks. However, many autonomous systems will rely on machine learning and ways to address this are urgently needed.

ESRs 12, 13, and 14 all start from a specific application scenario, i.e., autonomous vessels, clinical conversational bots and autonomous vehicles, respectively. In addition, they always consider other, possibly conflicting, design constraints, as is the case in industrial practice. ESR12 wants to assure safe autonomous sailing from A to B while minimizing operational costs by combining a cost-optimization algorithm, a collision-avoidance algorithm and situational awareness. ESR13 looks at the safety assurance for clinical conversational bots by combining safety engineering with typical clinical processes. ESR14 will cover the whole dependability assurance for autonomous vehicles, covering, besides safety, also reliability, availability and cyber-security.

Last, but certainly not least, ESR15 will take up the emerging challenge of the liability aspects of autonomous systems in safetycritical domains. ESR15 will propose a liability allocation framework for safe autonomous systems that explores new avenues for the allocation of liability for autonomous systems in a way that strikes a balance between the commercial interests of operators and manufacturers and the safety and fair compensation of the general public.

Coordinators for ETN SAS: Prof. Davy Pissoort (KU Leuven)
Davy.pissoort@kuleuven.be
+32 (0) 50 66 48 49 & +32 (0) 477 39 74 61

Prof. Jeroen Boydens (KU Leuven)
Jeroen.boydens@kuleuven.be
+32 (0) 50 66 48 03 & +32 (0) 486 79 63 9

Appendix 1: Recruitment Procedure and Principles

The search for appropriate candidates is initially based on normal recruitment strategies (e.g., publication on ec.europa.eu/euraxess, etc.; personal contacts of the network partners). All the recruitment is in line with the European Charter for Researchers, providing the overarching framework for the roles, responsibilities of both the researchers and employers. The Code of Conduct for the Recruitment of Researchers functions as a set of principles and ensures that the selection procedures are transparent and fair. The recruitment strategy for SAS will fully comply with the Code of Conduct’s definition of merit. For example, merit is not just measured on researchers’ grades, but on a range of evaluation criteria, such as team work, interdisciplinary knowledge, soft-skills and awareness of the policy and economic impact of science. The Recruitment Committee has members of each gender and considers the promotion of equal opportunities and gender balance as part of the recruitment strategy. Special efforts are made to attract women and ESRs from new EU Member States.

The pre and final selection will be made in a collective progress, led by the Recruitment Committee (RC), which consists of all the people who will be involved in the supervision process. Every member of the RC will be made aware of factors like unconscious gender bias. The candidates can apply for a maximum of three projects and list their order of preference. The 30 most suitable are invited to a Recruitment Workshop (Bruges, Belgium). In order to facilitate their travel, selected candidates (from outside Belgium) receive a fixed, lump sum of 250 euro (paid by the prioritised Supervisor). In order to avoid delays in reimbursements, candidates are asked to keep all invoices and tickets (cf. train, plane, hotel...).

Each candidate will give a presentation and be interviewed. Candidates will be given a domain-relevant peer-reviewed paper (prior to the recruitment event) by their prioritised Supervisor and will be asked questions about this paper during the interview to check if the candidate has the right background/profile for the ESR position. Prior to the recruitment event, skype interviews between the Supervisors and the candidates are recommended, along with online personality tests.

The committee will select the ESRs (1) based on their scientific background and potential, (2) based on the expected benefit of scientific exchange between the trainees’ home countries and institutions and the hosts, and (3) in accordance with gender equality and minority rights. The candidates will be ranked and a collective decision made, taking into account the order of preference. In this way a complementary team of ESRs can be assembled. The ESRs are employed on fixed-term contracts and are registered as staff candidates for PhD degrees. Therefore, they are entitled to pension contributions, paid holidays, and other employment benefits, as governed by the universities, non-academic partners and industrial companies.

In case not all 15 ESRs can be recruited during the collective Recruitment Event, the recruitment procedure is “decentralised”, meaning that the involved supervisors continue the search for good candidates. The GC is kept informed at all times when new eligible candidates appear. The GC makes an official complaint in case the Code of Conduct for the Recruitment of Researchers is breached. The involved supervisor is then expected to find another candidate. Recruitment problems are also, if still needed, discussed during the first SAS Network Wide Events (M7, M12) in order to deliver specific action plans to target specific networks relevant for the vacant ESR positions.

Continue reading

SUBSCRIBE TO JOBS LIKE THIS

  • Job types

62 JOBS FROM THIS EMPLOYER

KU Leuven
KU Leuven
Location: Leuven, Belgium
Electronic Design Of Sensor Networks For Health Applications
(Ref. ZAP-2017-44) Occupation : Full-time Place : Leuven Apply no later than : September 30, 2017 In the Science, Engineering and Technology Group, Faculty of Engineering Technology, Department of Electrical Engineering (ESAT), Technology Cluster Electrical...
KU Leuven
KU Leuven
Location: Leuven, Belgium | Closing on Sep 15
SIGNAL PROCESSING ALGORITHM DESIGN FOR NEXT-GENERATION NEURO-SENSOR TECHNOLOGY
(ref. BAP-2018-494) The work will be performed within the research division STADIUS ('Stadius Centre for Dynamical Systems, Signal Processing, and Data Analytics') at the Department of Electrical Engineering (ESAT) at KU Leuven, Europe’s most innovative university (Reuters,...
KU Leuven
KU Leuven
Location: Leuven, Belgium | Closing on Aug 31
POSTDOC POSITION ON BIOLOGY OF CO-OPERATIVE ONCOGENIC EVENTS IN ACUTE LYMPHOBLAS
(ref. BAP-2018-490) The laboratory for Disease Mechanisms in Cancer (Department of Oncology, KU Leuven) is looking for a motivated postdoctoral researcher. Our team has a long-standing interest in studying the biology of acute lymphoblastic leukemia (ALL), and in particular...
KU Leuven
KU Leuven
Location: Leuven, Belgium | Closing on Aug 26
BIG DATA IN AGRICULTURE
(ref. BAP-2018-486) The MeBioS Biophotonics group at the KU Leuven Department of Biosystems investigates the physical properties of biological materials to develop new technologies for the agro-food chain. The fundamental research activities focus on the measurement of the...