Martí Franquès Research Fellowship Programme

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Contracts for research groups
Trainee predoctoral researcher
In general, be in possession of an official undergraduate degree, or equivalent, and of a master degree, and have passed a minimum of 300 ECTS credits during the course of their official university studies, of which at least 60 must be master`s degree credits.
Department of Chemical Engineering
Learning Edit Costs in Non-Linear Graph Edit Distance
Francesc Serratosa Casanelles
Carme Julià Ferré
Graphs are abstract data structures used to model real problems with two basic entities: nodes and edges. Each node or vertex represents a relevant point of interest of a problem, and each edge represents the relationship between these points. Nodes and edges could be attributed to increase the accuracy of the model, which means that these attributes could vary from feature vectors to description labels. Due to this versatility, many applications have been found in fields such as computer vision, bio-medics, network analysis, and so on. During more than 30 years, researchers have been focused on how to represent objects through graphs and how to compute the distance between them. The definition of an adequate model for measure the dissimilarity between these representations is a key issue in pattern recognition, which is usually called Error-Tolerant Graph Matching. One of the most popular approaches in order to find a solution to this problem is the Graph Edit Distance, which estimates the distance between a pair of graphs computing the sum of costs of different edit operations that transform one graph into another. The distance is represented by a lineal equation that depends on the number of edit operations and the cost of these operations. The aim of this thesis is twofold. On the one hand, we will investigate how to convert the graph edit distance to a non-lineal equation. We assume that the non-linearity will make the distance to increase the ability to adapt to the problem at hand, thus, having more capacity to proper represent the object or more precisely, the distance between them. On the other hand, we want to develop a learning algorithm adapted to this new distance to learn the edit costs. The new methods and algorithms will be applied to discover the toxicity of chemical compounds, which are represented by attributed graphs. This research is going to be part of the European project “Computing infrastructure for the definition, performance testing and implementation of safe-by-design approaches in nanotechnology supply chains”, which has the code H2020-NMBP-TO-IND-2019-862195. Highly desirable attributes of the ideal candidate * Demonstrated previous experience in one or more of the following topics: Having participated in a research group * Hold a Master degree, or equivalent, in: mathematics or computer science * Language skills: English written and spoken * Specific Software skills: Matlab or python * Other skills: * Personality trait
Computer Science and Mathematics of Security
12 months
Full time
16450.20 €
37.5 hours a week
a determinar
01 December 2021
  1. Photocopy of identity card, resident`s card or passport currently in force
  2. Curriculum Vitae
  3. Photocopy of the certificate of the official academic qualification or proof of payment of the fees for the issuance of the certificate that allows the holder to access the doctoral studies. Students who are registered on an official university master`s course that allows them to access the doctoral programme during the 2021/2022 academic year must present a photocopy of their master`s course registration form.
  4. Academic transcript of the undergraduate degree issued in one of the following languages: Catalan, Spanish, English, French, Italian or Portuguese.
  5. Academic transcript of the master`s degree issued in one of the following languages: Catalan, Spanish, English, French, Italian or Portuguese. Candidates who have not completed their master’s degrees must send their provisional academic transcript.
  6. Declaration of equivalence calculated in accordance with the resolutions of 21 March 2016, 21 July 2016 and 18 September 2017 of the General Directorate of University Policy of the Spanish Ministry of Education, Culture and Sport or the resolutions that are effect at the moment when the application is presented
  7. Motivation letter (Optional)
  8. Reference letter (Optional)
  9. Accreditation of linguistic knowledge of English (Optional)
06 September 2021