University of Coruña - CITIC Hosting offer for a MSCA-IF post-doc candidate (Information Retrieval Lab Research Group)

Brief Description of the Institution

The University of A Coruña (UDC) is a public institution founded in 1989 whose primary objective is the generation, management and dissemination of culture and scientific, technological and professional knowledge through the development of research and teaching. Our current student population is approx. 23,000, there are over 150 research groups, and apart from its faculties, the university manages several Research Centres and University Institutes.

The Centre for Information and Communications Technology Research (CITIC) is one of the four research centres of the University of A Coruña, whose main objective is to promote the advancement and excellence in research, development and innovation in Information and Communications Technology (ICT) and to promote the transfer of knowledge and results to society. The CITIC is composed by more than 200 researchers who in the last year (2018) raised more than 4,5 M€ in competitive funds and academy-industry agreements, being a meeting point between the UDC research groups and ICT companies of the north of Spain. The scientific production of the Centre is highlighted, with more than 141 articles published in JCR journals, and 16 doctoral thesis defended, among others.

The three technological areas in which the main research expertise of the CITIC is developed are:

•    Data and Information Science: Big data, machine learning, statistics, mathematical models and simulation, information retrieval, text mining and natural language processing, GIS, document management systems and web information, quantum computing.
•    Perception, cognition and interaction: artificial intelligence, artificial vision, recommendatory systems and gamification, cybersecurity
•    Computer architecture, sensor and communications: High Performance Computing, Internet of Things, wireless communications, cloud computing, distributed systems

Brief description of the Research Group :

José Santos is full professor in the Department of Computer Science at the University of A Coruña. The research interests of his group include artificial life, bio-informatics, neural computing, evolutionary computing and autonomous robotics. In the last years, the research of the group was focused on computational biology, applying all the knowledge acquired in the other research lines to the computational modeling of biological problems. For example, one of the research objectives in computational biology was centered on the simulation of tumor growth in multicellular systems, including the analysis with the incorporation of cancer stem cells. Another objective of the group is the analysis of the optimality acquired in the biological evolution of the canonical or standard genetic code. Finally, one of the main research objectives of the group is related with different aspects of protein structure prediction and protein folding modeling. Bio-inspired meta-heuristics, especially evolutionary computing methods, were the main tools employed in the modeling of such problems. For instance, different evolutionary computing approaches were used in the prediction of protein structure in simple and detailed lattice models for protein representation, as well as atomic models. The group has ample experience in those research lines with different publications in top journals and in top-tier conferences, as well as the organization on events in those conferences.

Research / Project Description

This computational biology proposal is focused on the use of natural computing methods for modeling the protein folding problem. It pursues a different research line with respect to the ample research in protein structure prediction in two aspects to explore:

1. The previous and intense research is centered on predicting the final folded structure from the primary structure information. On the contrary, the proposal aims are focused on the modeling of the dynamic folding process, in order to comprehend the biological process that ends in the final fold.

2. The use of machine learning methods will allow to automatically infer the model of the folding process only from available resolved protein data (with known 3D structure), on the contrary to a priori (and non-exact) modeling of the physical interactions of protein components.

To develop these aims, the proposal considers protein folding as an emergent behavior, result of the local and temporal interaction between neighbor components. Connectionist systems for implementing extended Cellular Automata (CA) will be used, these being able to define the interactions of each amino acid to obtain a folded conformation, using discretized models for the spatial protein representation as well as detailed atomic models. This proposal will allow a generalization of classical CA, incorporating the advantages of connectionist models and it will allow the use of additional information of amino acids beyond the binary one of basic protein lattice models. It will be incorporated in the modeling the information of the secondary structure and, additionally, alternative evolutionary computing methods will be used to tackle the multimodal energy landscapes of the protein folding and for obtaining the neural CA that provide the folding.

Research areas (as established in MSCA):

•    Information Science and Engineering (ENG)
•    Life Sciences (LIF)

Who can apply?

At the deadline for the submission of proposals (11/09/2019), researchers:

•    shall be in possession of a doctoral degree
•    must not have resided or carried out their main activities in Spain for more than 12 months in the 3 years immediately prior to the above mentioned deadline.

Applications

Interested candidates are invited to contact Dr. José Santos Reyes (jose.santos@udc.es) by email before 31^st May 2019 indicating MCSA-IF 2019 in the subject line.

Documents to be submitted:

•    Resume (CV) describing your academic achievements and your research expertise, focusing on those aspects relevant in the context of this project.
•    Letter of motivation (including a brief description of his/her research interests)