PhD position in machine learning for mobility related data and applications

Data Transparency Group

Deadline for receipt of applications: July 1, 2024 23:59 AoE (02 July 2024, 13:59h Europe/Madrid Time)

Spatio-temporal and other mobility related data have been used in the past in scores of innovative applications ranging from city planning, to transportation, emergency, and health related services. The purpose of this PhD position will be to develop advanced privacy preserving algorithms and corresponding systems and demonstrators to tackle societal challenges as well as develop innovative new services in the areas of transportation, smart-cities, advertising, and e-health. The ideal candidate should be innovative in terms of bringing ideas in the area closer to reality, have strong data analysis and algorithmic skills, as well as desire to implement real-world systems for demonstrating the value of such ideas in realistic scenarios using real data.

 Requirements (as many as possible):

– Degree in Computer Science, Physics, Mathematics or related technical field.

– Strong background on developing distributed systems.

– Strong background on machine learning and algorithms.

– Knowledge on security and privacy.

– Proficiency in written and spoken English is mandatory.

– A desire to work on challenging topics and publish at top conferences is also mandatory.

 Related Pointers:

– E. Cabana, A. Lutu, E. Frias-Martinez, N. Laoutaris, “Improving Epidemic Risk Maps Using Mobility Information from Mobile Network Data,” ACM SIGSPATIAL’22. (extended abstract, full version at SpatialEpi’22 workshop).

– B. Cici, A. Markopoulou, E. Frias-Martinez, N. Laoutaris, “Assessing the potential of ride-sharing using mobile and social data: A tale of 2 continents and 4 cities,” ACM UbiComp’14. [pdf]

– B. Cici, A. Markopoulou and N. Laoutaris, “Designing an On-Line Ride-Sharing System,” ACM Sigspatial’15. [pdf]

The selected student will be supervised by Dr. Nikolaos Laoutaris Director of IMDEA’s Data Transparency Group.

Equal Employment Opportunity

IMDEA Networks Institute aims to increase the proportion of women and therefore qualified female applicants are explicitly encouraged to apply. Until a balanced ratio of men and women has been achieved at the institute, preference will be given to women if applicants have similar qualifications. IMDEA Networks Institute actively promotes diversity and equal opportunities. Applicants are not to be discriminated against in personnel selection procedures on the grounds of gender, ethnicity, religion or ideology, age, sexual orientation (anti-discrimination). People with disabilities who have the relevant qualifications are expressly invited to apply.