Assistant or Associate Professor in Planning & Decision Making for Autonomous Vehicles

2 Sep 2023
Job Information

Organisation/Company

Delft University of Technology (TU Delft)

Research Field

Technology

Researcher Profile

Leading Researcher (R4)
Established Researcher (R3)

Country

Netherlands

Application Deadline

15 Oct 2023 - 21:59 (UTC)

Type of Contract

Temporary

Job Status

Not Applicable

Hours Per Week

40.0

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 mission of the Cognitive Robotics (CoR) department at TU Delft is to develop intelligent robots and vehicles that advance mobility, productivity, and quality of life. The CoR department combines fundamental research with experimental work on physical demonstrators in areas such as self-driving vehicles, collaborative industrial robots, mobile manipulators and haptic interfaces. Of special interest are robotic solutions for complex, human-inhabited environments. Collaborations exist with cross-faculty institutes (TU Delft Robotics Institute and TU Delft Transport Institute), the national robotic ecosystem (RoboValley, Holland Robotics) and international academia and industry. Within the CoR department, the Intelligent Vehicles group covers the spectrum of machine perception, dynamics & control, and human factors for automated driving. It features a moving base vehicle simulator and a fully equipped experimental vehicle for automated driving, as well as relevant support staff.

We seek a highly qualified individual to join our faculty as an Assistant Professor (tenure-track) or Associate Professor (tenured) in the domain of Planning & Decision Making (PDM) for Autonomous Vehicles (AVs). This position offers the opportunity to develop cutting-edge PDM methods for mobile robotics and, in particular, for AVs. The aim is to have AVs navigate their traffic environment in a safe, comfortable and efficient manner. PDM can rely on inputs from on-board perception and map data, possibly extended by V2X communication (e.g. smart infrastructure, cooperative driving). The focus lies on modeling interactions with other road users in complex traffic scenarios. We seek an individual who is motivated to test the developed methods in the real-world (i.e. on-board our experimental vehicle, inputs from perception and map data can be provided by colleagues in the group) and who enjoys working together on realizing and advancing an AV "full-stack".

Specific topics of interest include, but are not limited to:

• Frameworks: graphical models (e.g. DBNs), Markov Decision Processes (e.g. RL / IRL), game theory, imitation learning, regression-based (e.g. neural networks), end-to-end (e.g. integration of perception and PDM)
• Use of auxiliary information w.r.t. on-board perception (e.g. map data, V2X)
• Combining high-level decision making and low-level motion planning
• Combining model- and data-driven approaches
• Addressing uncertainty from perception and from interaction with other road users
• Scenario mining
• Generalization to different environments
• Anomaly detection and self-assessment
• Safety verification and validation (simulation, on-board vehicle)
• Real-time capable frameworks for safe, comfortable and efficient navigation

Requirements
Specific Requirements

• PhD degree in Computer Science, Artificial Intelligence, Robotics, Electrical/Mechanical Engineering, or related discipline
• Experience in autonomous vehicles or mobile robotics
• Excellent track record in scientific research, as evident from publications in top-tier conferences and journals
• Ability to provide inspiring teaching at both undergraduate and graduate levels
• Ability and motivation to establish an own research direction within an interdisciplinary environment
• Organizational and managerial skills to interact and cooperate effectively with staff and other research institutes and organizations, including industry
• Proven ability in the acquisition of external funding (for Assoc. Prof. level)

TU Delft creates equal opportunities and encourages women to apply.

Additional Information
Benefits

This position is offered as an Academic Career Track position (0.8 – 1.0 FTE). During the Academic Career Track, we expect you to grow towards an Associate Professor position within a maximum of eight years, for which a position will be available. With other Academic Career Track colleagues, you will participate in the Academic Career Track Development programme, where you are offered ample opportunities to develop yourself in the areas of Education, Research, Societal Impact & Innovation, and Leadership & Organisation. You will regularly discuss your development and results with senior staff based on a personalized development and performance criteria agreed upon at the start of your Academic Career Track. You will start with a temporary contract that will be converted to a permanent contract no later than 12 -18 months after a positive evaluation, based on continuous confidence in your development potential and fit in the organisation. The salary for an Academic Career Track (Assistant Professor) position is min. €4.332,- to max. €6.737,- per month gross.

For exceptionally strong and experienced candidates, an Associate Professor position can be considered.
For an Associate Professor position different terms of employment apply. Depending on background and experience, the salary can range from min. € 6.002,- to max. €8.025,- per month gross. We offer an initial temporary position with the prospect of a permanent contract. The duration of the temporary position is a maximum of 1 year. After a positive performance assessment, you will be employed in a permanent Associate Professor position.

Inspiring, excellent education is our central aim. We expect you to obtain a University Teaching Qualification (UTQ) within three years if you have less than five years of teaching experience. This is provided by the TU Delft UTQ programme as part of the Academic Career Track Development programme.

TU Delft sets high standards for the English competency of the teaching staff. The TU Delft offers training to improve English competency. If you do not speak Dutch, we offer courses to learn the Dutch language within three years.

For international applicants, TU Delft has the Coming to Delft Service . This service addresses the needs of new international employees and those of their partners and families. The Coming to Delft Service offers personalised assistance during the preparation of the relocation, finding housing and schools for children (if applicable). In addition, a Dual Career Programme for partners is offered. The Coming to Delft Service will do their best to help you settle in the Netherlands.

Living conditions in the Netherlands (e.g. Delft, Hague, Amsterdam) are considered to be among the very best in Europe. The TU Delft scores consistently high in international comparisons (e.g. within top 15 in QS World Univ. Rankings 2023 in Engineering & Technology).

Selection process

Are you interested in this vacancy? Please apply before October 15th,2023 via the application button and upload:

• a motivation letter;
• a detailed CV;
• a research statement;
• a teaching statement;
• three selected publications, and
• contact data of three references.

A pre-employment screening can be part of the selection procedure.

You can apply online. We will not process applications sent by email and/or post.

Please do not contact us for unsolicited services.

Additional comments

For more information about this vacancy, please contact Prof. D. M. Gavrila (e-mail: d.m.gavrila@tudelft.nl ).

Website for additional job details

https://www.academictransfer.com/331806/

Work Location(s)

Number of offers available

1

Company/Institute

Delft University of Technology

Country

Netherlands

City

Delft

Postal Code

2628 CD

Street

Mekelweg 2

Where to apply

Website

https://www.academictransfer.com/en/331806/assistant-or-associate-professor-in-…

Contact

City

Delft

Website

http://www.tudelft.nl/

Street

Mekelweg 2

Postal Code

2628 CD

STATUS: EXPIRED