Monday, November 22, 2021

[DMANET] Funded 3-year PhD-student position (work contract) at URJC, Madrid, Spain: Combinatorial optimization and MAS applied to agrifleet coordination

[apologies for cross posting]


Context. The need for sustainable agriculture has led to the recent introduction of Agriculture Mobile Robots (AMRs) and Precision Agriculture (PA) that makes the practice of farming more accurate and efficient. The AMR research so far has focused on a single robot and its agriculture-specific capabilities. Very little work has been done in the domain of distributed, efficient, and scalable real-time agriculture vehicle fleet coordination in general and AMR fleet coordination in particular, considering the overall fleet performance as well as tactical and operational real-time vehicle, AMR, implement, and crop cultivating constraints. This topic is of high importance in the case of agriculture small and medium enterprises of limited funds that operate fragmentary and dispersed lands with precision farming and need to mutually collaborate in sharing of expensive AMRs for higher global competitiveness.


The doctoral research position is open at the Group of Artificial Intelligence (http://www.ia.urjc.es/GIA/) at the University Rey Juan Carlos (www.urjc.es/en ) within the Research Project "AGROBOTS: Scalable, Efficient and Decentralized Coordination of Automated Agricultural Vehicle Fleets" lead by Dr. Marin Lujak and funded by the Community of Madrid and University Rey Juan Carlos and including national and European academic partners from Spain, Italy, France, and the UK.


The expected outcome of the research is a PhD dissertation concerning the development of mathematical models and distributed, decentralized, and scalable algorithms for the agriculture fleet vehicle routing problem, a dynamic and decentralized variant of the vehicle routing problem. In the Project, we will study distributed and scalable Multi-Agent System (MAS) methods and techniques for agriculture vehicle dispatching and routing considering imperfect communication networks.


The work contract should start as soon as possible, preferably in February 2021 and should last for three years. You will receive an internationally competitive salary.


Eligibility criteria

The candidate is expected to have a master's degree or an equivalent in Computer Science, Industrial Engineering, Management Engineering, Applied Mathematics, or a related field with a strong academic background in Combinatorial Optimization. Furthermore, good programming skills (preferably experience with IBM ILOG Cplex Studio, Gurobi, MATLAB and/or Java) and a good knowledge of written and spoken English are requested.



How to apply

If you wish to apply for this work contract, you are kindly asked to send the following in the same order: 1) motivation letter with research interests and goals, 2) CV, 3) three recommendation letters with respective contacts, 4) copies of your diplomas and transcripts, 5) English proficiency certificate and other certificates (if any), and 6) relevant publications (if any) in one PDF file at the following e-mail: [marin dot lujak at urjc dot es ] preferably by December 15th 2021. The applications are considered on a rolling basis. For any further questions, please do not hesitate to contact me by email.

_____________________________________________
Dr. Marin Lujak
Distinguished Researcher Lecturer
Center for Intelligent Information Technologies CETINIA
University Rey Juan Carlos
Campus Móstoles (Madrid), Spain
Tel: +34 91 488 8281
Web: https://sites.google.com/view/marin-lujak/
marin.lujak@urjc.es | www.urjc.es | @URJC

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