15 PhD Positions in Socially Aware Robots through SWEET Project

Apply for 15 PhD positions in socially aware robots through the SWEET project, a Marie Skłodowska-Curie Industrial Doctoral Network.

Apply for 15 PhD positions as part of the SWEET project, a Marie Skłodowska-Curie Industrial Doctoral Network. The project aims to develop socially aware robots that can perceive, interpret, and respond to human emotions, intentions, and contextual differences.

The consortium, formed by 10 beneficiaries and 15 partner organizations, will offer an integrated curriculum encompassing theoretical knowledge and real-world application scenarios. Each PhD student will spend 50% of their contracted time in a mandatory secondment at other partners/beneficiaries.

Applicants should have a master’s degree in a relevant field, excellent grades, research talent, and personal ambition. They should also have excellent command of English, good academic writing and presentation skills, and be willing to spend time at other institutes/countries during the PhD thesis period.

Benefits include a competitive salary, outstanding training, integrated academy/industrial research activities, scientific advice from internationally recognized experts, and a solid mentoring strategy.

Eligibility criteria include not having resided or carried out main activity in the country of the institution that recruits the student for more than 12 months in the 3 years before the recruitment date.

Applications should be submitted via email in one PDF document, including the application form, copy of passport, full CV, short motivational video, letter describing previous research experience and current research interest, reference letters, transcripts of grades, and additional certificates (if any).

Selection of candidates will be performed via online interview, and positions will be offered after approval by the SWEET Committee.

Tags: PhD positions, SWEET project, socially aware robots, Marie Skłodowska-Curie Industrial Doctoral Network, robotics, artificial intelligence, machine learning