PhD Position Road safety prediction on the basis of ethically sound physiological measurements

8 Feb 2024
Job Information

Organisation/Company

National Technical University of Athens

Department

Department of Transportation Planning and Engineering

Research Field

Engineering

Researcher Profile

First Stage Researcher (R1)

Country

Greece

Application Deadline

16 Feb 2024 - 11:59 (Europe/Athens)

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

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

No

Offer Description

Within the IVORY doctoral network, this PhD position aims to understand and predict how the psychophysiological state of the driver contributes to overall road safety, particularly by using measurements of physiological data, such as the electrocardiogram (ECG), photoplethysmogram (PPG), blood pressure, among others. The goal is to create machine learning models that relate individual physiological dynamics with road safety indicators, with the ultimate objective of accurately and reliably detecting and warning, in real-time, when the driver is unfit for the driving task, regardless of automation level. Deep learning methodologies, such as convolutional neural networks, should be considered, as well as privacy-by-design frameworks.

The position contributes to road safety research by compiling a taxonomy of driver monitoring technologies, creating innovative algorithms for physiological-based, real-time prediction of driver capability and its impact on safety, in several real-world scenarios, and to explore and create frameworks to assess the ethical and privacy dimensions of the use of driver monitoring technologies.

IVORY (ivory-network.eu) 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:

National Technical University of Athens (NTUA) Athens, Greece

School of Civil Engineering, Department of Transportation Planning and Engineering

Months 19-36 of PhD

Industry host:

CardioID Technologies Lda, Lisbon, Portugal

Months 1-18 of PhD

Secondment(s):

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

Duration: 4 months

 

Requirements

Research Field

Engineering

Education Level

Master Degree or equivalent

Skills/Qualifications

• A Master's degree (or equivalent) in transport engineering / data science with a background (ideally BSc) in civil engineering / computer science
• Familiarity with big data in transport applications
• Familiarity with road safety / human factors
• Experience with data analysis (statistical analysis, machine learning, etc.)
• Applicants with MSc in human factors and with demonstrable data handling skills can also apply
• 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
• Coding skills in Python programming language
• 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 8.0 / TOEFL: minimum 100 

  • Doing a PhD at NTUA 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.

Specific Requirements

Familiarity and hands-on experience with handling physiological signals (e.g., electrocardiogram, photoplethysmogram, electroencephalogram, electrodermal activity). • Capacity to conceptualize and conduct experiments to collect physiological data. • Familiarity with concepts related to human factors engineering. • Familiarity with machine learning algorithms, deep learning, and dynamic modeling. • Familiarity with advanced statistics (statistical tests and regression) and probability theory (probability distributions, Bayesian statistics). • Familiarity with concepts related to ethical and fair use of machine learning systems. • Familiarity with concepts related to data protection and privacy (e.g., GDPR). • Coding skills in Python. • Familiarity with Python libraries and frameworks for signal processing and machine learning (e.g., numpy, pandas, scikit-learn, tensorflow, keras, pytorch). • Familiarity with Git version control

Languages

ENGLISH

Level

Excellent

Research Field

Engineering » Civil engineering

Additional Information
Benefits

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), and is very competitive overall.

In addition, the doctoral candidate will benefit from extensive 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.

Website for additional job details

https://www.nrso.ntua.gr/ntua-marie-curie-new-phd-vacancy-road-safety-predictio…

Work Location(s)

Number of offers available

1

Company/Institute

National Technical University of Athens

Country

Greece

State/Province

Zografos

City

Athens

Postal Code

15773

Street

Iroon Polytechniou 24

Where to apply

E-mail

[email protected]

Contact

State/Province

Zografos

City

Athens

Website

https://www.nrso.ntua.gr/

Street

Iroon Poytechniou 24

Postal Code

15773

E-Mail

[email protected]

STATUS: EXPIRED