PhD Position Explainable AI for Road Safety – Benchmarking AI Methods and Data

8 Jan 2024
Job Information

Organisation/Company

Delft University of Technology

Department

Faculty of Technology, Policy & Management

Research Field

Engineering

Researcher Profile

First Stage Researcher (R1)

Country

Netherlands

Application Deadline

31 Jan 2024 - 23:59 (Europe/Amsterdam)

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

36-40

Offer Starting Date

1 May 2024

Is the job funded through the EU Research Framework Programme?

HE / MSCA

Reference Number

TUD04869

Marie Curie Grant Agreement Number

101119590

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

No

Offer Description

Would you like to make an impact in the reduction of road traffic fatalities around the world? Are you ready to become one of the future leading researchers in the field of AI in road safety? 

Job description

Within the IVORY doctoral network, this PhD position aims to disentangle the strengths and weaknesses of two types of analytical methods in road safety research i.e. statistical and econometric methods and machine learning algorithms and understand their performance and optimally integrate both techniques with benchmark datasets and applications in road safety for decision support.

The position contributes to road safety research by creating a taxonomy of explainable AI methodologies and their applications in road safety, developing a model-agnostic methodological framework for integrating ML algorithms and statistical/econometric methods, and demonstrating the applicability of the framework by creating a new explainable AI-based risk mapping tool for urban roads in the West Midlands region in the UK.

IVORY  is a Horizon Europe MARIE SKLODOWSKA-CURIE ACTION Industrial Doctoral Network consisting of 22 partners (universities, industry, and non-governmental organizations). The project aims to develop a new framework for the integration of AI in road safety and train a new generation of leading researchers in the field, in order to address the UN Sustainable Development Goals target 3.6 (halving the number of traffic fatalities by 2030) and EC ‘Vision Zero’ strategy (eliminating traffic fatalities by 2050).

PhD students will obtain their PhD degree from the relevant academic partner, and spend at least 50% of their PhD time at the relevant non-academic partner.

Academic host:

Delft University of Technology (TU Delft), Delft, The Netherlands

Faculty of Technology Policy and Management

Months 1-18 and 37-48 of PhD

Industry host:

Agilysis, Banbury, United Kingdom, Month 19-36 of PhD

Agilysis (https://agilysis.co.uk/ ) is a leading transport safety consultancy who provide strategic support and data platforms to local authorities, road safety partnerships and roads policing throughout Great Britain and across the globe. Specialising in Safe System methodology, Agilysis have supported national governments and transport authorities to develop and deliver on new strategies to help them achieve their Vision Zero goals. They have an extensive track record of working with public and private sector clients to deliver perceptive and relevant studies using state of the art techniques, including multidimensional data mining, socio demographic segmentation, geo-spatial methodology and contextualisation. With access to a wide variety of datasets such as live and historical connected vehicle data, the Agilysis team provide insightful and rigorous analysis of trends in road traffic collisions and the people involved in them.

Secondments:

Transport West Midlands, United Kingdom, Duration: 3 months

Requirements

Research Field

Engineering

Education Level

Master Degree or equivalent

Skills/Qualifications

 

• A master's degree (or equivalent) in transportation engineering / data science with a background (BSc) in civil engineering, computer science, mathematics, economics, or statistics
• Applicants with a master's degree in behavioural sciences and with demonstrable econometrics skills can also apply
• Experience with advanced statistics (econometric models) and probability theories (probability distributions, Bayesian paradigm, etc.)
• Familiarity with machine learning algorithms
• Coding skills in Python or R
• Strong conceptual and analytical skills
• Strong motivation and some experience to undertake research
• Excellent writing and presentation skills
• The ability to work both independently and as part of a team
• High level of proficiency in English:
  • Proof of English language proficiency at a Common European Framework of Reference (CEFR) level of C1, or an MSc degree in English, or IELTS: minimum 7.0 / TOEFL: minimum 100 

  • Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements .

Specific Requirements

Optional skills (preferred but not required):

• Familiarity with road safety / traffic behaviour
• Hands-on experience with machine learning algorithms

Languages

ENGLISH

Level

Excellent

Research Field

Engineering

Additional Information
Benefits

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 3 employment contracts. An initial 1,5 year contract at the academic host with an official go/no go progress assessment within 15 months. Followed by an additional contract at the industry host for the for the next 1,5 year assuming everything goes well and performance requirements are met. At the end, another 1 year contract at the academic host, with the same conditions

The successful candidate will receive an attractive salary following the MSCA regulations for doctoral candidates. The exact salary will vary depending on the country of the host partner and will be confirmed upon appointment. The salary includes a living allowance, a mobility allowance, and a family allowance (if the recruited doctoral candidate has or acquires family obligations during the duration of the fellowship).

In addition, the doctoral candidate will benefit from further training within the IVORY network, which includes internships/secondments in other laboratories, a variety of training courses (including transferable skills), and active participation in workshops and conferences.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme  for partners and they organise events to expand your (social) network.

Eligibility criteria

• A Master's degree (or equivalent);
• Not in possession of a doctoral degree at the date of the recruitment;
• Recruited applicants can be of any nationality and must undertake trans-national mobility (i.e., move from one country to another) when taking up the appointment. In particular, at the time of selection, the recruited applicant for this position must not have resided or carried out their main activity (work, studies, etc.) in the Netherlands for more than 12 months in the 3 years immediately prior to their recruitment. Short stays, such as holidays, are not taken into account.

Selection process

Are you interested in this vacancy? Please apply no later than 31 January 2024 via the application button and uploa:

• Detailed CV, including information on the candidate’s proficiency in English;
• Motivation letter (1 page), describing why the position fits the applicant;
• Contact information of 2 references who may be contacted at a later stage in the procedure.

Please note: 

• 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.

Website for additional job details

https://ivory-network.eu/index.php/recruitment/

Work Location(s)

Number of offers available

1

Company/Institute

TU Delft University / Faculty of Technology, Policy & Management

Country

Netherlands

State/Province

Zuid-Holland

City

Delft

Postal Code

2628 BX

Street

Jaffalaan 5

Geofield

Where to apply

Website

https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobI…

Contact

State/Province

Zuid-Holland

City

Delft

Website

https://www.tudelft.nl/en/tpm/

Street

Jaffalaan 5

Postal Code

2628 BX

E-Mail

[email protected]

Phone

+31 15 27 84 913

STATUS: EXPIRED