The program's Study program has 60 ECTS credit
26 ECTS credit - work end of Master's Degree
22 ECTS credit - Compulsory subjects
12 ECTS credit - Electives
MODULES, SUBJECTS AND SUBJECTS
| MODULE | SUBJECT | SUBJECT | OP/OB | ECTS CREDIT |
| 1 work End of Master's Degree |
1.1 | OB | 26 | |
| 2 General |
2.1 | OB | 2 | |
| 2.2 Science of data and models in experimental sciences. |
OB | 5 | ||
| OB | 5 | |||
| 2.3 Introduction to Bioinformatics |
OB | 5 | ||
| OB | 5 | |||
| 3 Elective |
3.1 Electives |
OP | 3 | |
| OP | 3 | |||
| OP | 3 | |||
| OP | 3 | |||
| OP | 3 | |||
| OP | 3 | |||
| OP | 3 | |||
| OP | 3 | |||
| OP | 3 | |||
| OP | 3 | |||
| OP | 3 |
project end of Master's Degree
The Master's Degree has an orientation internship: from the first day, each student will start a project on his or her area of interest to apply in a real case the IT tools explained in the subjects.
The TFM (26 ECTS credit) is a work directed by a tutor, who must first meet with the student. It begins on the first day of the course and constitutes the pivot around which the Master's Degree revolves.
Many researchers at the University of Navarra and research center Applied Medicine (CIMA) offer TFM degrees that they are willing to supervise. Alternatively, the student can look for a professor willing to supervise a work of his/her interest and propose it as a TFM. In addition, there are agreements in place with companies interested in hosting a student from Master's Degree to conduct their TFM at business.
TFM Proposals
project nº1
iterative proteindesign for genetically encoded polymers (GEPs)
Director: Juan Pablo Fuenzalida
project nº2
Analysis of microproteins to identify new antitumor therapies
Director: Puri Fortes
project nº3
AI-based computational pathology to identify cell types and neighborhoods
Director: Carlos E de Andrea
Co-director: José Echeveste
project nº4
assessment of the contact pressure patterns of different regions of the human body
Director: Diego Maza
project nº5
Aggregation of structured data
Director: Jorge Elorza
project nº6
Spatio-temporal models for the prediction of suicidal behavior
Director: Miguel Valencia
Co-director: David Galicia
project nº7
development of new selective adsorbent materials and their application in water treatment
Director: Francisco Javier Peñas
Co-director: Adrián Benito
project nº8
Automation in the detection of landmarks in mammalian cranial Structures for the analysis of morphological patterns.
Director: David Galicia
project nº9
Analysis of the sensitivity of different SDM procedures to degradation of accessible biological and environmental information
Director: David Galicia
project nº10
Exploring evolutionary relationships in the animal kingdom through molecular traits: controversial phylogenies and cryptic species
Director: David Galicia
Co-director: Isabel Rey
project nº11
Assesing functional host-microbiome-diet interactions using deep learning models
Director: Rafael Valdés
project nº12
Defining the core healthy human microbiome using deep learning models
Director: Rafael Valdés
SOME EXAMPLES
Automated image analysis diagnostic system
The project aims to develop a low-cost diagnostic kit to detect, by means of image analysis on a biological sample , certain diseases that are particularly prevalent in poor countries (tuberculosis, malaria, etc.).
Analysis of the sensitivity of different species distribution models to the degradation of biological and environmental information. available
To know the limitations that the most frequently used methods in the literature have on the quality of the information on entrance, in order to decide which is the most appropriate tool to use depending on the primary data available.
Precision personalised medicine for the treatment of multiple myeloma using Deep Learning techniques
In this project we propose to use data of RNA-Seq, DNA-Seq and clinical data to design a new stratification system for multiple myeloma patients based on the employment of autoencoders.
Modelling catalytic photodegradation kinetics in aqueous media
The work will consist of developing general kinetic models of photodegradation that take into account other substances present in the aqueous medium.
