General

Autonomous engineering systems are being developed at high pace worldwide with examples being autonomous vehicles, drones and robotics for manufacturing, care, cure, agricultural and domestic applications. Both industry and society foster high expectations on the future impact of autonomous systems. Industrial examples are fully automated distribution of goods in harbors, warehouses and factory floors, and the automated inspection of crops in agriculture. Societal impact is envisioned, e.g., in automated highways or in hospitals where surgery robots cooperate with surgeons or patient support systems reaching higher levels of autonomy aiming at cost reduction and improved care or city-wide parcel delivery by drones. In general, system autonomy allows, on the one hand, to take the (expert) human out of the loop to achieve increased performance, safety and efficiency of engineering systems, while, on the other hand, it allows such systems to interact in more complex, real-world environments where interaction with (non-expert) humans is actually required. Both aspects will allow for a step change in the pervasiveness of engineering systems in industry and society.

System autonomy is often achieved by some form of task automation (perception, decision-making and action). Automation and control systems are commonly perceived as 'artificial intelligence' (AI) if these are capable of adapting to and interacting with their environment in a smart way. Such interaction with their environment (both technology and humans) typically takes place by data-exchange (e.g., by sensing and/or data-base access) and physical interaction (e.g., interaction with humans). In this sense, systems can be made more 'intelligent', by making their automation strategies adaptive to such real-life data and interactions. A further synergy of model-based control techniques on the one hand and data-based learning techniques, from the field of artificial intelligence, on the other hand is envisioned to be the key enabler for such artificially intelligent, autonomous systems.

Research field

The further development of artificially intelligent autonomous systems, however, poses many challenges, on sensing, control, world modelling, human-machine interaction, hardware & software design, and (big) data management and algorithmic design. Another key aspect is that of the adaptability of such systems. When operating in the real world, uncertainties, faults and hazards are unavoidable and systems need to be able to automatically adapt to ensure safety and security or to ensure optimal performance. Research in this field requires an inherently multi-disciplinary approach relying on expertise not only from mechanical engineering, but also from electrical engineering and computer science (a.o., artificial intelligence).

Algorithms with artificial intelligence (AI), such as machine and deep learning, can generally deal with complex systems and data sets. However, typically no guarantees on system behavior (stability, performance, optimality, safety, etc.) are provided for the resulting AI algorithms. A synergy between artificial intelligence and systems and control can be envisioned to develop smart, learning automation strategies that can both deal with highly versatile and complex systems and processes while providing certificates on system behavior.

Within the Department of Mechanical Engineering, long-standing application-related research lines are being maintained on topics that, on the one hand, would benefit from developments in the scope of Autonomous Systems and Artificial Intelligence and, on the other hand, would serve as excellent ways to valorize such research in relevant application domains, such as , e.g., autonomous and cooperative driving, precision-agriculture (high-tech to feed the world), robotics and mechatronics, digital twin for smart industry & advanced manufacturing, high-tech systems, health applications, smart energy systems, automation of distribution centers, acoustics, smart materials, etc.

This research theme provides ample opportunity for fundamental, interdisciplinary research and valorization in a wide range of applications, many of which are strongly rooted in the Dutch high-tech & manufacturing industry, and the agriculture and transportation sectors.

Research field candidates

The Department of Mechanical Engineering of the TU/e seeks to hire four (4) outstanding faculty members at all levels within the field of Autonomous Systems and Artificial Intelligence, which should play a leading role in addressing these challenges and trends in the above-mentioned areas. Core disciplines that are envisioned to be needed are:

Dynamical Systems and Control,

Artificial Intelligence & machine learning,

Autonomous monitoring and smart diagnostics

Experimental techniques; networks of distributed sensors and actuators.

Sensing and world modelling, human-machine interaction,

Systems engineering, equipment and system design,

Knowledge on relevant application domains such as, for example, robotics, mechatronics, transport systems, health applications, smart industry, energy, agricultural systems, etc.

Candidates can apply to (tenure-track) assistant, associate and full professor positions and are expected to be experienced in at least one of the core disciplines mentioned above. She/He should have the ambition to contribute to the creation of a strong, internationally renowned research group, while fostering a collaborative network with other academics working on the topic within the department, the university and industry. The candidate should contribute to the progress in the field of autonomous systems and/or artificial intelligence, in order to be able to make the step to further penetration of system autonomy in industry and society.

Education

The candidate will contribute to the existing BSc program Mechanical Engineering and the MSc programs Mechanical Engineering (ME) and Systems and Control (S&C) within the department.

Financing

Four (4) positions of 1.0 fte, financed by the Mechanical Engineering Department.

Embedding

The candidate's group will strongly co-operate with existing groups in the Department, in particular the groups within the sections of Dynamics and Control and Control Systems Technology. Depending on the function level to which the candidate applies, the candidate's group can be embedded in the Section of Dynamics and Control, the Section of Control Systems Technology or could form a new section within the department. The department fosters a personnel strategy stimulating personal growth towards faculty forming independent groups within larger coherent sections.  

The candidate's group will be embedded in the High-Tech Systems Institute within the University. The group will also be embedded in research schools of the Dutch Institute of Systems and Control (DISC) and Engineering Mechanics (EM).

Function elements

Teach the education components of the education program;

Teach periodic maintenance of the assigned education components;

Indicate improvement possibilities for the assigned education components;

Carry out independent research for the purpose of science, companies - where possible - government and the business sector.

Contribute to the recruitment of second and third flow of funds;

Provide specific guidance to the academic personnel in carrying out research;

Provide leadership to work groups, committees or project teams in the groups.

These function elements hold for researchers at an assistant professor level. For candidates at Associate Professor level or Full Professor level, additional elements and elements at a higher level are expected.

Function demands

University education in Mechanical Engineering, Electrical Engineering or Computer Science;

Academic doctorate;

Relevant research experience in the field of study;

Extensive teaching experience (including PGO education, lectures and tutorials, practice, mentoring final projects and internships);

Management qualities for the capacity to independently initiate second and third flow of funds and to provide leadership in this;

Scientific creativity and production;

Good communicative and didactic skills.

These function demands hold for researchers at an assistant professor level. For candidates at Associate Professor level or Full Professor level, additional demands and demands at a higher level are expected

A challenging job in a dynamic and ambitious university.

A position on Assistant/Associate/Full Professor level. The type of position depend on the profile of the candidate.

The gross monthly salary is in accordance with the Collective Labor Agreement of the Dutch Universities (CAO NU), depending on your experience.

An attractive package of fringe benefits, including excellent work facilities, child care, moving expenses, sports facilities, an extra holiday allowance (8% in May), and an end-of-year bonus (8.3% in December).

Women in Science

TU/e strives towards a diversified workforce at all function levels. Part of this endeavor is to appoint more talented women to scientific positions. The Women in Science (WISE) network at TU/e is very actively promoting to share knowledge and experience which may further assist newly appointed female scientific staff in their further professional and personal development.