Contents

Doctorate in Computational Biology

The PhD Program in Computational Biology invites you to explore a transdisciplinary field where biology, mathematics, physics, and computer science converge to tackle complex challenges in both the natural and social sciences. This field combines theoretical and computational tools to study biological systems across multiple scales—from molecules to populations—incorporating cutting-edge advances in artificial intelligence, molecular modeling, bioinformatics, biological networks, and computational neuroscience.

Information

Degree

PhD/Doctor in Computational Biology

Application Period

Closed

Duration

8 semesters

Start Date

March 2024

Modality

Presential

Program Description

The PhD Program in Computational Biology invites you to explore a transdisciplinary field where biology, mathematics, physics, and computer science converge to tackle complex challenges in both the natural and social sciences. This field combines theoretical and computational tools to study biological systems across multiple scales—from molecules to populations—incorporating cutting-edge advances in artificial intelligence, molecular modeling, bioinformatics, biological networks, and computational neuroscience.

As a student, you will join a dynamic research community and develop skills to lead projects, analyze large-scale data, formulate impactful scientific questions, and effectively communicate your findings. The program equips you to contribute to frontier research across disciplines, opening career paths in academia, public service, biotechnology, and tech industries.

Program Objectives

The PhD Program in Computational Biology aims to train independent researchers of the highest level with a deep knowledge of the foundations of computational biology as it relates to bioinformatics, molecular modeling, network theory, machine learning and population dynamics. Thus, it provides students with the ability to perform cutting-edge and innovative research in an autonomous, responsible and ethical manner for the generation of new knowledge.

Lines of Research

Lines of research:
  • Computational Neuroscience, Data Science and Artificial Intelligence.
  • Computational biophysics of macromolecular systems.
  • Genomic Biology, Bioinformatics and Biological Networks.
Research Topics
  • Complex Systems.
  • Neuromorphic Computation.
  • Computational Biophysics of Macromolecules.
  • Evolution of Artificial Societies.
  • Structure and Dynamics of Complex Networks.
  • Data Science and Artificial Intelligence.
  • Genomic Biology and Bioinformatics.
  • Computational Neuroscience.

Profile of Graduates

The graduate of the PhD in Computational Biology at Universidad San Sebastian, is a researcher who:

  • Generates new knowledge through experimental research with a solid background in fundamental biological technologies and their implications in Computational Biology.
  • Develops interdisciplinary research projects, leading research teams, with the highest levels of excellence, rigor and ethics, applying methodologies relevant to Computational Biology and Bioinformatics.
  • Formulates scientific questions for the advancement of knowledge in any of the research lines related to computational biology.
  • Performs innovative teaching in higher education according to the student-centered teaching-learning process.
  • Communicates knowledge and research results through publications in specialized journals.
  • Links scientific knowledge with the concerns and needs of society and transmits it in an understandable way to the general public and other specific groups.

Curriculum

Admission Process

Application

Applicants must submit their academic background through the digital platform of the Doctoral Program in Computational Biology of Universidad San Sebastian.

Requirements

Applicants must send their academic background through the digital platform of the Doctoral Program in Computational Biology of Universidad San Sebastian. The documentation must certify the following requirements:

  • Academic degree of Bachelor, Master or Professional Degree in Basic Sciences, Biomedical Sciences or any area of knowledge with the ability to contribute to the development of research in the area of Computational Biology. In case of having academic degrees of foreign origin, these must be equivalent to those mentioned, according to the International Classification of Education (ISCED-UNESCO), in force at the date of application.
  • Certification of grades of undergraduate and other studies, including those of advanced and postgraduate studies. The evaluation scales used and the minimum passing grade must be clearly specified.
  • Certificate of placement ranking of the graduates of the graduating cohort in their undergraduate and graduate studies. If the university does not issue this certificate, a letter from the institution will be required.
  • Curriculum vitae that accredits previous studies, presentations at congresses, research publications, among other activities.
  • Two letters of recommendation from academic professionals, sent confidentially via e-mail to the Doctoral Program address.
  • Statement of purpose that includes the formulation of a relevant topic of interest for study and research during the program, as well as the committed dedication.
  • The applicant must specify his/her interests and research objectives in the short and long term, through a letter, whose length should not exceed 800 words.
  • Photocopy of both sides of identity card or passport, valid at the time of application.

The process for the selection of applicants consists of the evaluation of the applicant’s background, a personal interview and a knowledge test. In the case of applicants who reside outside the country or cannot travel to Santiago, the interview, examination and presentation will be conducted by videoconference.

Annual cost

Referential values 2025

  • Tuition: $393.900
  • Fee: $3.847.700

Benefits

Ask about applying for tuition scholarships, fees and maintenance benefits.

Graduates

  • Sergio Hernández Galaz, Academic Degree PhD in Computational Biology (2025).
    Thesis: “Unveiling cellular heterogeneity in renal cell carcinoma by geometric deep learning”.
    Tutor: Dr. Alberto Martin Martin.
    Co-tutor: Dr. Álvaro Lladser Caldera.