Program access information

Objectives

The PhD Program in Computer Science is born from a synergy between the research lines in software of the Department of Computer Systems and Informatics (DSIC) and in hardware of the Department of Computer Systems and Computer Informatics (DISCA).

The main objective is to train PhDs in the field of Computer Science, with the capacity to carry out research, development, innovation and technology transfer, as well as to direct or collaborate with other researchers and professionals in their field of competence.

The training objectives of the program allow students to obtain a multidisciplinary and generalist training, or to deepen their knowledge in one of the four areas that make up the Official Postgraduate Program in Computer Science:

• Parallel and Distributed Computing (DSIC)
• Computer Engineering (DISCA)
• Software Engineering, Formal Methods and Information Systems (DSIC)
• Artificial Intelligence, Shape Recognition and Digital Imaging (DSIC)

The PhD Program in Computer Science is aimed at students who wish to acquire advanced knowledge in computer science to perform responsible tasks in industry, administration or academia.

Entry Profile

Students entering the doctoral program must comply with the requirements established in the R.D 99/2011 of January 28th. Regarding the requirements of the program itself, in relation to the academic qualifications, those Spanish or foreign graduates with training in computer engineering, telecommunications engineering, industrial engineering, electronic engineering, mathematics and physics will be able to access the program. In relation to postgraduate training, applicants must have passed at least 60 credits of postgraduate training (Master’s degree) in the field of Computer Science. The Academic Committee of the program will determine the degree of affinity of the postgraduate degree provided with any of the Master’s degrees offered by DSIC or DISCA and, if necessary, may establish training complements.

Profile of graduates

PhD in Computer Science, specialized in one of the fields indicated in the objectives.

The PhD program is organized, designed, coordinated and supervised by the Academic Committee (AC) responsible for its definition, updating and quality, as well as training and research activities. This committee is composed of 5 to 6 members in addition to the program coordinator, all of them PhD professors of the UPV (from the Department of Computer Systems and Computing and the Department of Computer and Systems Informatics) and research staff from one of the research structures involved in the PhD program.

The number of members of each research structure that is part of the CA will depend on the number of theses presented in the last five years by each structure participating in the doctoral program. All members of the committee have at least one six-year period of recognized research.

It will be the CA who will ensure compliance with the program admission criteria and will be responsible for its evaluation, taking into account the following aspects:

1. Academic qualifications: Spanish or foreign graduates with degrees in computer engineering, telecommunications engineering, industrial engineering, electronic engineering, mathematics and physics are eligible for the program.
2. Postgraduate training: it must be accredited to have passed at least 60 credits of postgraduate training (Master’s degree) in the field of Computer Science.
3. Academic transcript: both undergraduate and graduate academic transcripts must be provided to be evaluated by the CA.
4. Complementary training: the admission of the student may include the requirement of complementary training when the CA considers it necessary, depending on the student’s previous training.

The CA of the program will be responsible for evaluating the admission of students by applying a valuation index (IV) on a scale of 0 to 100 points. Those who exceed an IV of 70 points will be admitted to the doctoral program. The IV will be calculated as indicated in the following cases:

Assumption 2.1

In the case of having previously completed at least 60 credits at the Master’s level, the following equation will be applied:

IV = 10 * f_exp + 40 * f_gra + 50 * f_pos

where:

• f_exp: weighting factor of the academic record of the total of studies (undergraduate and graduate) considering the overall average grade on a standardized scale from 0 to 1.
• f_gra: weighting factor of the degree title
• f_pos: postgraduate degree weighting factor

The values of f_gra are specified in the following table:

Title	f_gra
Computer Engineering	1
Telecommunications Engineering Electronics Engineering Mathematics	[0.75-1.00]
Industrial Engineering Physics	[0.50-0.75]

For those degrees whose weighting factor is specified as a range, the CA will be responsible for the evaluation of this factor according to the following criteria:

• If the degree has a specialization, the CA will assess the affinity of such specialization to the field of Computer Science.
• Adequacy of the degree program studied to the line of research in which the candidate shows interest.

Regarding postgraduate training, given the wide diversity of possible Master’s degrees in the field of Computer Science, the Academic Committee of the program will determine the degree of affinity of the postgraduate degree with one of the Master’s degrees offered by DSIC or DISCA, thus establishing a weighting factor (f_pos) between [0,1]. The Master’s degrees offered by DSIC and DISCA are:

• Parallel and Distributed Computing (DSIC)
• Computer Engineering (DISCA)
• Software Systems Engineering and Technology (DSIC)
• Artificial Intelligence, Shape Recognition and Digital Imaging (DSIC)

Thus, the final assessment of f_pos will be in accordance with the following principles:

• All graduate degrees will receive a weighting factor between [0.1] according to the Academic Committee’s evaluation.
• Master’s degrees offered by DSIC or DISCA will receive a weighting factor equal to 1 (f_pos=1).
• A Master’s degree that receives a weighting factor of less than 0.4 (f_pos < 0.4) will not pass the IV >= 70 condition.

Only those who meet a score of f_pos=1 would be exempt from taking complementary training courses, and would be able to directly access the doctoral program.

Otherwise, depending on the undergraduate and graduate training provided, the CA will determine the additional training that the PhD student should take in order to be admitted to the PhD program. These training complements may be acquired through the training offer of one of the Master’s degrees mentioned above, all of them official degrees of the UPV with related contents that allow complementing the training required to ensure the success of the doctoral training. Specifically, the recommendation of the CA to define such training will consist of taking subjects from one or several subjects from one of the four Master’s degrees taking into account the student’s training weaknesses and the line of research in which he/she shows interest in participating (e.g. Artificial Intelligence, Language Technologies, Software Engineering, Computing Technology, Grid Computing, Emerging Network Technology, etc.).

The subjects to be taken will be broken down into the corresponding subjects with an indication of their credits and associated training activities:

• Directed training activities (lectures, seminars, group work presentations, etc.)
• Supervised training activities (tutorials, review of assignments, etc.)
• Autonomous training activities (personal study, bibliographic or documentary compilation on a research topic, etc.).
• Formative evaluation activities (tests, oral presentations, work reports, etc.)

Assumption 2.2

In the case of not having previously taken credits at the Master’s level and being in possession of an official Spanish Bachelor’s degree of at least 300 ECTS credits, the following equation will be applied:

IV = 20 * f_exp+ 80 * f_gra

Where f_exp is the weighting factor of the academic record of the undergraduate studies considering the overall average grade on a normalized scale from 0 to 1 and f_gra is the weighting factor of the undergraduate degree, the value of which is given as shown in the table presented for assumption 2.1.

Those who are assessed under this assumption must take compulsory complementary training. As in case 2.1, these training complements may be acquired through the training offer of one of the above-mentioned Master’s degrees.

For assumptions 2.3 (degree obtained under foreign educational systems) and assumption 2.4 (being in possession of another Spanish PhD degree), the CA will study the applicants’ records and will determine the training complements to be carried out, if this were the case, being able to use weighting factors similar to those shown in the previous tables, and always guaranteeing the training capacity of the doctoral student to undertake the initiation in research tasks.

The academic committee of the program, after studying the curriculum of the doctoral student, will decide whether it is appropriate for him/her to take complementary training courses. Where appropriate, it will define the list of subjects to be taken from the university’s postgraduate academic offer, considering the specific training required by the doctoral student for the proper development of his or her research work.

In particular, the complementary training in the case of the PhD in computer science will typically be chosen from among the subjects offered by one of the four master’s degrees associated with the PhD:

• Master in Parallel and Distributed Computing (DSIC, UPV)
• Master’s Degree in Computer Engineering (DISCA, UPV)
• Master’s Degree in Software Systems Engineering and Technology (DSIC, UPV)
• Master in Artificial Intelligence, Shape Recognition and Digital Imaging (DSIC, UPV)

Basics

• Systematic understanding of a field of study and mastery of research skills and methods related to that field.
• Ability to conceive, design or create, implement and adopt a substantial process of research or creation.
• Ability to contribute to the expansion of the frontiers of knowledge through original research.
• Ability to critically analyze, evaluate and synthesize new and complex ideas.
• Ability to communicate with the academic and scientific community and with society in general about their fields of knowledge in the modes and languages commonly used in their international scientific community.
• Ability to promote, in academic and professional contexts, scientific, technological, social, artistic or cultural progress within a knowledge-based society.

Personal skills and abilities

• To develop in contexts where there is little specific information.
• Find the key questions to be answered to solve a complex problem.
• Design, create, develop and undertake novel and innovative projects in their field of knowledge.
• Work both in a team and autonomously in an international or multidisciplinary context.
• Integrate knowledge, deal with complexity and make judgments with limited information.
• Intellectual criticism and defense of solutions.

Other competencies

• Ability to acquire a theoretical and practical mastery of the fundamental concepts in some of the research lines of the program, in the field of computer science.
• Ability to identify, model and solve problems in some of the research areas of the program, in the field of computer science.
• Ability to acquire advanced scientific knowledge and initiate research work in some of the research areas of the program, in the field of computer science.
• Ability to transfer own techniques and results in some of the research areas of the program, in the field of computer science.
• Ability to pose and propose solutions to highly complex IT problems.
• Ability to integrate IT technologies, applications, services and systems in multidisciplinary contexts.
• Ability to manage bibliographic resources and locate documentation on previous work on the topic of interest.
• Ability to plan, structure and adequately write a report on a computer work.
• Ability to propose and develop original contributions that can be published in forums of recognized prestige in the field of computer science.
• Ability to perform coordination tasks in scientific meetings on the subject of interest.