[DMANET] Fully-funded PhD positions at DIEM (Department of Information and Electric Engineering and Applied Mathematics) - University of Salerno

The Department of Information and Electric Engineering and Applied Mathematics at the University of Salerno has openings for fully-funded PhD researchers. The Automatic Control Group at the University of Salerno is looking for outstanding candidates in the following areas.

1. Decision-making under uncertainty for autonomous agents

What we are looking for: a talented, outstanding PhD researcher with a Master degree (or close to completion) in Systems and Control, or Computer Science, or related field, with interests in System Theory, Optimal Control and Reinforcement Learning.

General project description: this program investigates the design of autonomous agents able to make optimal decisions (i.e. craft a control policy) directly from data, possibly crowdsourcing information from third parties. As such, the candidate will conduct theoretical and algorithmic research on probabilistic data-driven optimal control. It is expected that our methodologies will have a broad range of applicability and we will explore the possibility of benchmarking our decision-making algorithms against specific applications from biology, smart cities and robotics. The research will develop and build upon tools from optimal control, information science and reinforcement learning.

Position supervised by: Prof. Giovanni Russo (https://sites.google.com/view/giovanni-russo/ <https://sites.google.com/view/giovanni-russo/>)

2. Control of very-large-scale systems

What we are looking for: a talented, outstanding PhD researcher with a Master degree (or close to completion) in Complex Systems, or related field, with interests in the physics of large-scale systems and distributed control.

General project description: the candidate will conduct theoretical and algorithmic research on the control of very-large-scale systems. Specifically, we will investigate how to control network systems for which only a macroscopic description is known (e.g. via partial differential equations). These systems abound in nature and technology and we will apply our results to analyze and control multi-vehicle and biochemical systems. The research will develop and build upon tools from nonlinear control and information theory.

Position supervised by: Prof. Giovanni Russo (https://sites.google.com/view/giovanni-russo/ <https://sites.google.com/view/giovanni-russo/>)

3. Multi-agent learning

What we are looking for: a talented, outstanding PhD researcher with a Master degree (or close to completion) in Complex Systems, or related field, with interests in Distributed Learning/Optimization and Human-Robot Coordination.

General project description: this program investigates the design of multi-agent systems able to learn iterative tasks. As such, the candidate will conduct theoretical and algorithmic research on the design of multi-agent systems able to learn how to cooperatively perform complex, repetitive, tasks. The key application focus for the algorithms will involve the design of autonomous agents (e.g. robots) able to cooperate with humans in order to fulfil a joint task. The research will develop and build upon tools from distributed optimization, decision science and multi-agent systems.

Position supervised by: Prof. Giovanni Russo (https://sites.google.com/view/giovanni-russo/ <https://sites.google.com/view/giovanni-russo/>)

4. Optimal control of robots in presence of actuation limits and interaction forces

What we are looking for: a computer/automation/robotics engineer with a knowledge of robotics fundamentals (kinematics, dynamics, trajectory planning), robot control (motion/interaction control), robotic systems programming (ROS or other robotic software framework), mastery of MATLAB and C++ programming. The candidate should understand the basics of machine learning. Previous experience with optimal control (e.g. dynamic programming), planning algorithms (e.g. randomized algorithms), model-less control and model identification is a plus. Good mastery of English language is mandatory (at least B2 CEFR).

General project description: Kinematic redundancy is key for optimization of motion and interaction tasks of robotic systems. It is a resource to devise optimal behaviors which often require the robotic system to work in close proximity of kinematic and actuation limits (like in time-optimal control). For non-redundant systems moving in free space, several ad-hoc control paradigms exist, but it is reasonable to assume that more efficient techniques can be designed for redundant systems. The problem becomes even more complex when forces are exchanged between robots and/or with the environment, as when robots physically interact with a jointly manipulated object. We are keen to investigate hybrid optimal control/machine learning solutions to tackle this research issue with a motivated robotics enthusiast.

Position supervised by: Prof. Pasquale Chiacchio (https://docenti.unisa.it/001888/en/home <https://docenti.unisa.it/001888/en/home>)

5. Resilient control against cyber-attacks

We are looking for a talented, outstanding PhD researcher with a Master degree (or close to completion) in Systems and Control, or Computer Science, Complex Systems, or related field, with interests in distributed control of cyber-physical systems (CPSs).

General project description: the candidate will conduct theoretical and algorithmic research on enforcing safety specifications on spatially distributed control systems. Specifically, there is a great potential in this area for developing novel approaches using methodologies that pertain to discrete event systems (DESs). Indeed, cyber-attacks act essentially at the higher levels of the control architecture, where the discrete event view of the system is the most effective description of the system dynamics. The project aims not only at extending the current state of the art from a systems theory point of view with novel contributions, but also to apply and validate the proposed methodologies in the context of CPSs using case studies that emphasize the social and economic impact.

Position supervised by: Prof. Francesco Basile (https://docenti.unisa.it/005630/en/home <https://docenti.unisa.it/005630/en/home>).


TO APPLY, please email giovarusso@unisa.it <mailto:giovarusso@unisa.it> with subject line "PHD positions", clearly specifying the title of the project you are interested in. Also, attach:

- curriculum vitae;

- statement of motivation and research interests (1-page max);

- transcripts of all exams taken and obtained degrees (in English);

- names and contact information of up to two references.

Additional information: while knowledge of the Italian language is not mandatory, to facilitate international students in settling down, an introductory Italian language course will be offered. Moreover, based on the outcome of the interviews, students might be offered a free accommodation at the University of Salerno Campus and a free meal per day at the canteen. Other benefits include funding for 3.000,00 euros to support his/her research needs and financial support to spend research periods at other international institutions.



Giovanni Russo
Associate Professor

Senior IEEE Member
AE for IEEE Transactions on Control of Network Systems
Website: https://sites.google.com/view/giovanni-russo/home <https://sites.google.com/view/giovanni-russo/home>
Twitter: @GRusso_UniSa <https://twitter.com/GRusso_UniSa>

University of Salerno
Dept. of Information and Electrical Engineering and Applied Mathematics (DIEM)


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