Sign up with your email address to be the first to know about new products, VIP offers, blog features & more.

PhD Positions on Planning and Scheduling at the Information Engineering and Computer Science department of the University of Trento

ApplyTime

PhD positions in Computer Science and Artificial Intelligence at the Department of Information Engineering and Computer Science of University of Trento in challenging projects to develop new algorithms for planning, scheduling and acting under uncertainty, and making these operate in industrial (e.g. manufacturing, intra-logistics) and civil (e.g. hospital, pharmaceutical) relevant environments.
Are you interested in developing new algorithms, extending state-of-the-art AI techniques, and prepared to take-on real-life problems involving advanced automation and robotic applications collaborating with humans?
Join us in a team that considers the operational planning, scheduling and actuation (motion planning) of advanced robotic platforms (AGV, UAV, …) to orchestrate their operations in collaborating with human to achieve complex business relevant objectives like e.g. reduce time-span, optimize resource consumption, quickly adapt to contingencies (e.g. product and/or platform faults, changes in objectives, changes in human operations). As the capabilities (e.g. dexterity) of robotic agents grows and their adoption in solving complex tasks collaborating with humans increases together with an increase in the complexity of the objectives, the problems of finding feasible plans to orchestrate the different agents, and of dynamically adapt and react to run-time contingencies to fulfill the high level objectives are becoming more and more difficult.
The main tasks for the PhD student are to work on algorithms and artificial intelligence techniques from the fields of constraint programming, mathematical optimization, path planning, evolutionary algorithms and/or reinforcement learning i) to solve such planning, scheduling, actuation (motion planning) and reactive adaptation problems; ii) to deepen our understanding of these techniques; iii) and to show how they can be successfully combined to solve problems of industrial and civil relevance. Moreover, the PhD student will be allowed to experiment the developed techniques and algorithms in realistic-size facilities (e.g. Robotic Labs at the University, and industrial facilities joint with the University of Trento) equipped with state-of-the-art robotic and automation platforms.
Please apply through the Admission link (https://ict.unitn.it/education/admission/call-for-application) on this websitehttps://ict.unitn.it
Deadline for application: 16 June 2020, 4:00 Italian Time (GMT +2)
Interested candidates shall also contact Prof. Marco Roveri marco.roveri@unitn.it and to Prof. Luigi Palopoli luigi.palopoli@unitn.it.
Requirements————–
Applications for the PhD Program in Information and Communication Technology are accepted from applicants who hold:
– an Italian “Laurea magistrale” instituted in conformity with Italian   Ministerial Decree 270/2004, or
– a university degree of the previous regulations (Italian “Laurea   specialistica ” or “Diploma di Laurea”), or
– an equivalent degree obtained abroad (Master’s degree) and   recognized as equivalent to the Italian “Laurea magistrale” by the   Admissions Committee for the sole purposes of admission to the   Doctoral programme, also within the framework of mobility and   cooperation inter-university agreements.
Applications are also accepted from students who expect to complete their degree by October 31, 2020.
Scholarship————–
The PhD position will be covered by scholarships.  Currently the annual gross amount of the doctoral scholarship is approximately €16.290,00. The scholarship net amount may change, depending on the country of residence and on country-specific taxation agreements.
Students who have been awarded a PhD scholarship are entitled to get a 50% increase of their scholarship when staying abroad for reasons related to their doctoral research and studies.
Each student is provided with a budget which can be used for educational and research purposes.
First year students have the priority for getting accommodation at student residences.

ApplyTime_Positions