PhD Position in Data Science

Funding: funded according to the Swiss rates (50,000 CHF / 55,000 USD / 45,000 EUR annually)
Start date: Spring 2021, or later
Awarding university: University of Franche-Comté, Besançon, France
Location: Research to be carried out in the University of Applied Sciences and Arts of Western Switzerland (HES-SO/HEIG-VD), Yverdon-les-Bains, Switzerland
Activity: Almost 100% of time spent on research (very little or no teaching load)
Duration: up to 4 years

We have a PhD position in a new exciting European research project in collaboration with CHUV (Centre Hospitalier Universitaire Vaudois), the University of Franche Comté, CHU (Centre Hospitalier Universitaire) Besançon, TechWan ( and Maincare ( The main objective of the study will be to find optimal solutions to guide and involve the most appropriate vector (helicopter, ambulance) in the face of an emergency, accident or disaster. When only one vector is involved (e.g. ambulance) route planning in a vehicular network is a well known problem. Static solutions to find the shortest path have proven their efficiency, however in a dynamic network such as a vehicular network, multiple vectors, multiple locations, one has to deal with dynamic costs (travel time, consumption, waiting time, …), time constraints (traffic peaks, ghost traffic jam, accidents …), availability of vectors (helicopters non available because of their involvement on disaster sites), the problem is much more complex to solve. Emphasis will also be placed on the efficient use of available resources. For moderately severe cases, it is often preferable to use a vector that is not the closest, but the one which minimizes the redistribution of the vectors on the territory. It is therefore necessary to determine which means to be used, knowing that these will be mobilized for a certain time and that it will no longer be possible to use them. During an intervention, it should not be forgotten that resources will be mobilized, perhaps to the detriment of another incident that may occur at the same time. The topology of the terrain on the route and the place of the intervention, as well as the density of the population where the intervention takes place, as well as the density of the population where an ambulance will have to be moved, must be taken into account. AI (deep learning) algorithms will have to be tested, adapted, and improved to tackle the problems described above. If good and innovative solutions are found they will certainly have a positive impact on our society, and potentially save lives.

Switzerland ranks among the best places to live in the world, especially due to personal safety, natural beauty and its infrastructures. The working atmosphere is very motivating and open. Our offices are located in the largest technological park in Switzerland, in the heart of one of the most dynamic regions of the country in terms of innovation.

PhD students are full employees, with standard salaries and paid holiday. They will be supervised by a group of researchers specialized in machine learning and optimization. Our working language is English, and there is no need to learn French.


  • MSc in mathematics or theoretical physics (possibly related to data science and machine learning algorithms) with excellent academic records
  • Good knowledge of Python, Java or a similar programming language
  • Excellent writing and verbal communication skills, as well as presentation skills. Besides proficiency in English, creativity, curiosity, innovative and independent thinking is a must. He shows motivation to collaborate in an interdisciplinary international team, to participate in training programs, and is willing to travel to present his work to international conferences

More information:

  • Stephan Robert,

Applications, including a resume (incl. academic grades), and the name of at least three references (physical and email addresses, phones numbers) should be sent as soon as possible to (MS Word, .pdf, .ps or plain text). Applications will be handled confidentially.

Internships and Master Projects

I am happy to give internships and Master projects (min. 6 months, preferably mathematicians with very good skills in CS) to motivated non-HEIG-Vd students. If you do want to do an internship or a Master project with me, please send me a resume with your academic records and work or project experience, and explain me your motivation.