What you'll study
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AI Techniques for Data Analysis
12 CFU - code 146466
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Advanced Human and Microbial Genetics
6 CFU - code 146426
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Computational Structural Biology
6 CFU - code 146427
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English C1
3 CFU - code 146046
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Genetic and Metabolic Engineering
6 CFU - code 145658
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Genomic Data Science in Health and Disease
12 CFU - code 146428
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Multiscale RNA and Protein Omics
12 CFU - code 146429
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Network-based Data Analysis
6 CFU - code 145573
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Quantum mechanics
6 CFU - code 146323
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Regression and Classification Models
6 CFU - code 146045
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Final thesis
21 CFU - code 146436
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Internship
6 CFU - code 145933
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Technology Innovation for the Production of Biotechnological Products
6 CFU - code 146430
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Bio-Inspired Artificial Intelligence
6 CFU - code 145763
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Biomolecular Simulations
6 CFU - code 146432
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Foundations of Entrepreneurship in Biotech and Pharma
6 CFU - code 146103
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Knowledge Graphs
6 CFU - code 146391
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Modeling and Simulation of Biological Systems
6 CFU - code 146431
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Ageing
3 CFU - code 146344
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Animal models in Biomedical Research
3 CFU - code 146325
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Biotechnology Challenge
6 CFU - code 146195
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Cancer Genomics
6 CFU - code 145495
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Medicinal Chemistry
3 CFU - code 146343
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Multiscale Modeling and simulation of soft and biological matter
6 CFU - code 146435
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Scientific skills beyond research
3 CFU - code 146111
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Advanced Concepts in Human and Microbial Genetics
3 CFU - code 146433
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Applied Programming for Biological Data Analysis
9 CFU - code 146434
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Biostatistics
12 CFU - code 145539
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English C1
3 CFU - code 146046
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Genetic and Metabolic Engineering
6 CFU - code 145658
-
Genomic Data Science in Health and Disease
12 CFU - code 146428
-
Multiscale RNA and Protein Omics
12 CFU - code 146429
-
Network-based Data Analysis
6 CFU - code 145573
-
Quantum mechanics
6 CFU - code 146323
-
Regression and Classification Models
6 CFU - code 146045
-
Final thesis
21 CFU - code 146436
-
Internship
6 CFU - code 145933
-
Technology Innovation for the Production of Biotechnological Products
6 CFU - code 146430
-
Biomolecular Simulations
6 CFU - code 146432
-
Computational Structural Biology
6 CFU - code 146427
-
Foundations of Entrepreneurship in Biotech and Pharma
6 CFU - code 146103
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Machine learning
6 CFU - code 145062
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Modeling and Simulation of Biological Systems
6 CFU - code 146431
-
Ageing
3 CFU - code 146344
-
Animal models in Biomedical Research
3 CFU - code 146325
-
Biotechnology Challenge
6 CFU - code 146195
-
Cancer Genomics
6 CFU - code 145495
-
Medicinal Chemistry
3 CFU - code 146343
-
Multiscale Modeling and simulation of soft and biological matter
6 CFU - code 146435
-
Scientific skills beyond research
3 CFU - code 146111
The Master’s Degree in Quantitative and Computational Biology equips you with advanced interdisciplinary competencies to understand, analyse and model complex biological systems through quantitative and computational approaches.
You will develop a deep understanding of molecular and cellular biology and learn how to integrate biological knowledge with mathematics, statistics, physics and computer science to address real-world challenges in biotechnology and biomedicine.
Throughout the programme, you will acquire:
- Advanced scientific programming skills for analysing large-scale biological datasets
- Statistical inference and multivariate modelling for high-dimensional omics data
- Machine learning and artificial intelligence methods applied to genomics, transcriptomics and clinical data
- Multi-omics data integration techniques for extracting meaningful biological insights
- Mathematical and computational modelling of dynamic biological systems
- Biological network analysis and systems-level interpretation of complex processes
- Computational structural biology and molecular modelling for studying biomolecular interactions
- Simulation methods for investigating biological phenomena across different scales
You will also learn how to:
- Design reproducible computational workflows and bioinformatics pipelines
- Critically evaluate data quality, model assumptions and methodological limitations
- Transform large and heterogeneous datasets into biologically and clinically relevant knowledge
- Formulate quantitative hypotheses and test them through in silico experimentation
- Work effectively in interdisciplinary teams at the interface of biology, medicine and data science
Strong emphasis is placed on analytical thinking, problem solving and scientific communication.
By the end of the programme, you will be able to independently design and manage research or innovation projects in data-driven life sciences, operating confidently in both academic and industrial environments.
Teaching methods include:
- Lectures
- Computational laboratories
- Project-based learning
- Journal clubs and seminars
- Team-based interdisciplinary work
Strong emphasis is placed on:
- Hands-on computational training
- Reproducible research practices
- Integration between experimental and computational approaches
The second year is largely devoted to internship and thesis research, allowing students to work in cutting-edge laboratories or innovative companies, in Italy or abroad.
Career Opportunities
Graduates are prepared for high-level positions in:
- Biotech and pharmaceutical industries
- Computational drug discovery
- Clinical genomics and precision medicine
- AI-driven healthcare companies
- Bioinformatics and omics technology companies
- Research institutes and innovation centers
- Data science roles in life sciences
Professional profiles include:
- Computational Biotechnologist
- Bioinformatician
- Computational Biologist
- Biological Data Scientist
- Computational Biophysicist
The degree prepares students for professions classified as:
- Biologists and related professions
- Biotechnologists
- Bioinformaticians
- Data analysts and statisticians
- Research scientists in life sciences
Advanced studies and research
Graduates can pursue PhD programmes in:
- Biomolecular Sciences
- Computational Biology
- Systems Biology
- Bioinformatics
- Biophysics
- Artificial Intelligence for Health
Graduates are competitive for international doctoral programmes in Europe and beyond.