Quantitative and Computational Biology (QCB) University of Trento

Overview

Introduction

The Master of Science (Laurea Magistrale) in Quantitative and Computational Biology is a multidisciplinary degree that formally integrates quantitative sciences and applied biology, thanks to the involvement of the following organizations at the University of Trento :

• CIBIO, Centre for integrative biology

• Department of Physics

• Department of Mathematics

• Department of Information Engineering and Computer Science

The course focuses on a strategic area where technology and methodology enable students to face essential questions at the interface between fundamental research and clinical and pre-clinical areas, through analytical and quantitative approaches.

The Master is entirely taught in English and is designed to capture the increasing need for researchers and experts able to transform the enormous amount of biological information ("big data") into knowledge, as well as to gain quantitative insight into the behavior of biological systems by means of bio-mathematical and biophysical models.

Key target areas include pharmacogenomics, biotechnology, food science and precision medicine, which represent applied research fields where the growing availability of multidimensional data demands high interdisciplinarity. 

Program Overview

The Master’s Degree in Quantitative and Computational Biology (QCB) offers advanced training at the intersection of life sciences, data science, artificial intelligence, and quantitative modeling. The program equips students with the conceptual and technical tools to extract knowledge from complex biological data and to build predictive, mechanistic, and data-driven models of biological systems.The curriculum combines rigorous training in programming, data analysis, and modeling with a solid foundation in molecular and cellular biology, enabling students to translate biological questions into formal quantitative frameworks and implement scalable computational solutions.A defining feature of QCB is its integrated approach: students from different backgrounds progressively converge toward a shared profile in quantitative and computational biology, gaining the ability to design analytical workflows, develop bioinformatics tools, and build predictive models that bridge experimental research and state-of-the-art computational methodologies.The program fosters critical thinking, interdisciplinary teamwork, and research autonomy, preparing graduates for careers in academic research and in data-driven environments across biotechnology, pharmaceuticals, and biomedical innovation.

Admissions

How to apply

• Access the online application form

• Upload the required documents

• Submit your online application by the deadline

Requirements

• Bachelor’s degree (or equivalent) in Biotechnologies or in any related field as described in the call for admission

• English at the B2 level of the Common European Framework of Reference for Languages

Selection criteria

• Assessment of previous studies and their coherence with the MSc

• Academic curriculum

• Statement of purpose

Curriculum

The Master’s Degree in Quantitative and Computational Biology is a two-year program (120 ECTS) structured to progressively build advanced interdisciplinary expertise at the interface of biotechnology, computational sciences and quantitative modeling.

The curriculum is organized to ensure both flexibility and coherence, combining foundational training, specialization and research experience.

First Year

The first semester includes core interdisciplinary courses shared by all students, alongside a differentiated component designed to complement their previous academic background.

During this initial semester:

• students with a computational or quantitative background strengthen their expertise in artificial intelligence applications in biology and structural bioinformatics;

• students with a biological or biotechnological background reinforce their skills in mathematics, statistical inference and scientific programming for biological data analysis.

All students attend courses in:

• human and microbial genomics;

• population genetics and evolutionary models;

• transcriptomics and proteomics data analysis;

• systems biology and modeling of biological networks;

• machine learning and data-driven approaches in biomedicine.

The first year establishes a strong shared quantitative and computational foundation while consolidating molecular and cellular biology knowledge.

Second Year

The second year focuses on specialization and profile personalization. Students can select elective courses to deepen specific areas such as:

• advanced artificial intelligence techniques for biological systems;

• computational biophysics and biomolecular simulations;

• network modeling and systems-level analysis;

• biotechnology innovation and regulatory aspects.

The program includes a compulsory internship (6 ECTS), which may be carried out within University laboratories, research institutions or biotechnology and pharmaceutical companies in Italy or abroad.

The final semester is entirely dedicated to the preparation of a research-based Master’s thesis (21 ECTS). The thesis involves original research activity under the supervision of a faculty member and may be conducted in academic or industrial settings, both nationally and internationally.

Teaching activities include lectures, computational laboratories, project-based work, journal clubs and research seminars, fostering critical thinking, teamwork and independent scientific reasoning.

Program Outcome

• The Master’s Degree in Quantitative and Computational Biology aims to build a highly specialized scientific and professional profile capable of integrating experimental biology with quantitative and computational approaches.

• Graduates will be able to:

• understand complex biological phenomena at molecular, cellular and systems levels through interdisciplinary integration of biology, mathematics, physics, statistics and computer science;

• generate, analyze and integrate large-scale omics datasets (genomics, transcriptomics, proteomics and multi-omics);

• design and implement computational pipelines and bioinformatics resources;

• develop statistical and machine learning models for predictive and mechanistic analysis of biological processes;

• build and simulate mathematical models of dynamic biological systems;

• critically evaluate the assumptions, strengths and limitations of computational and quantitative models;

• apply artificial intelligence tools to biomedical data analysis and precision medicine contexts.

• The program prepares graduates to operate in multidisciplinary environments, collaborating effectively with biologists, clinicians, engineers, data scientists and industry professionals. They acquire the ability to communicate scientific results clearly and rigorously in English, both orally and in writing, and to present complex data using appropriate digital tools.

• Graduates are trained for professional roles such as computational biotechnologist, bioinformatician, computational biologist, biological data and systems analyst, and computational biophysicist. Career opportunities include academic research, doctoral programs, biotechnology and pharmaceutical industries, biomedical data science, healthcare genomics and advanced research laboratories in both public and private sectors.

• The program also equips students with the autonomy and critical thinking skills necessary for lifelong learning and for adapting to the rapidly evolving landscape of quantitative life sciences.

Career Opportunities

• Graduates in Quantitative and Computational Biology are trained to operate at the interface of biotechnology, data science and quantitative modeling, combining experimental knowledge with advanced computational expertise.

• The program prepares professionals capable of designing, analyzing and interpreting high-dimensional biological data, developing predictive models and implementing artificial intelligence solutions in biomedical and biotechnological contexts.

• Graduates may pursue careers in roles such as:

• Computational Biotechnologist

• Bioinformatician

• Computational Biologist

• Biological Data and Systems Analyst

• Computational Biophysicist

• Graduates can find employment in:

• biotechnology and pharmaceutical companies, particularly in R&D, computational drug design, precision medicine and target validation;

• hospitals and healthcare institutions implementing genomics, digital health and personalized medicine approaches;

• public and private research centers specializing in functional genomics, systems biology, computational biology and biostatistics;

• companies developing bioinformatics platforms, AI-based biomedical tools and data-driven healthcare solutions;

• startups and spin-offs in life sciences, digital genomics and bio-digital technologies;

• high-performance computing centers supporting life science applications.

• The program also provides a strong foundation for admission to PhD programs in quantitative biology, bioinformatics, biotechnology, computational biophysics and related interdisciplinary fields.

• Graduates are equipped to work in multidisciplinary teams alongside biologists, clinicians, engineers and data scientists, contributing to innovation in the rapidly evolving landscape of biotechnology for health and precision medicine.