Msc Mathematical Sciences for Biomedical Data and Biophysics

Context

 Why computational biology is the future ?

The human genome contains 3 billions nucleotides and this code is read by each of the 3.7 1013 cells present in our body to perform a plethora of molecular, cellular and physiological functions, many of which are impaired in disease states. This complexity is increasingly explored by biologists using high throughput technologies which produce an unprecedented amount of data. The analysis, interpretation, integration and usability of this exponentially growing information have consequently become major issues for biology and medicine in the XXIst centrury. Within this context, computational biology is a fast developing multidisciplinary approach that combines methodologies stemming from mathematics, physical sciences and computer sciences to address these new challenges and ultimately understand the complexity of biological systems and diseases.

 

Why learning computational biology at Université Côte d’Azur ?

Université Côte d’Azur (UCA) is strongly committed to research with more than 4000 persons involved in top ranked laboratories. UCA was awarded in 2016 the prestigious IDEX governmental grant to accelerate the development of pluridisciplinary research. With the presence of five large Research Institutes of Biology (iBV, C3M, IPMC, IRCAN and ISA) together with the Math Department (LJAD),  two large Computer Science Institutes (INRIA and i3S) and the institute of physics (InPhyNi) you will learn computational biology in a cutting edge, dynamic and open scientific environment.

Objectives

Learning from experience

Prospective students with a background in mathematics, physics or computer sciences will be trained to tackle computational biology problems in a scientific, evidence-based manner as well as have the opportunity to gain experience working in a true multidisciplinary mindset. To this end, every student will be immersed in multidisciplinary research through intense problem-solving and project-based learning as well as continuous collaboration with researchers developing computational biology projects at UCA.

 

A comprehensive set of skills in quantitative and computational biology

Our approach is to propose a coherent set of courses in the fields of Mathematics, Physics and Computer Science dedicated to the study of biological systems and data. Upon completion of the training, students will master relevant theoretical and methodological concepts in areas ranging from :

  • Mathematical and computational methods
  • Bioinformatics
  • Modelling approaches to study biochemical and biophysical processes in cell and tissues
  • Analysis and interpretation of large datasets generated by high-throughput technologies (omics, single cell, imaging, signals)

Program

Organisation

The 2 years program (120 ECTS) covers:

  • Molecular, Cell and Tissue Biology;
  • Bioinformatics;
  • Systems Biology;
  • Biophysics ;

Formal methods range over:

  • mathematical modeling;
  • data science.

Some of the lectures will be shared with the UCA Msc Data Science and Artificial Intelligence. Experience of academic research will be gained through internships and rotations in teams from UCA or from outside institutes.

"Learn by doing" training constitutes more than 1/3 of the total volume, including a 6 month internship during the 2nd year.

 
 

First year (M1)

Semester 1

  • Biology 6 ECTS

      Basics in cell and tissue biology

      Advanced cell and tissue biology

  • Bioinformatics 6 ECTS

       Introduction to biological database organization and digging; nucleic acid and protein structure and functions

       Algorithms for Computational Biology

  • Data Science 6 ECTS

       Processing large datasets with Python

       A general introduction to data mining

  • Systems Biology and biophysics 9 ECTS

       Systems biology modeling biochemical networks - deterministic approaches

       Structural bioinformatics & biophysics

       Biophysics: physical biology of the cell

  • Misc 3 ECTS

       Methodological approaches

       Scientific communication

       Ethical issues and laws

 

Semester 2

  • Bioinformatics 7 ECTS

      Genome assembly and annotations

       Read mapping and counting

       Detecting and analyzing genetic variations

  •  Data Science 9 ECTS

       Machine learning: from theory to practice

       Theory of statistical learning

        Model selection and resampling methods

  •  Systems Biology and biophysics 5 ECTS

       Stochastic approaches to model biochemical networks

       Fundamentals of bioimage informatics

       Techniques for the acquisition of Biodata

  •  Biology 1 ECTS

        Conference series

   

Second year (M2)

Semester 1

  • Bioinformatics 7 ECTS

       The genome in action: from bulk to single cell analyses

       The genome in action: epigenomics

       Multiomics: combining heterogenous data & application to cancer genomics

  • Data Science 10 ECTS

       Statistical learning

       Statisctical analysis of graphs

       Signal processing 

  • Systems Biology and Biophysics 12 ECTS

       Application cases

       Methodological advances

Semester 2

  • Internship: 6 months project in research laboratory (30 ECTS)

Course list

Careers

 After completion of this 2 years Master training in computational biology at UCA, graduated students will have opportunities to work either as research scientists in the academic field or as R&D engineers in private pharma and biotech companies, CRO or large hospitals.

Their multiple skills profile will help them to apply to a variety of jobs worldwide in areas ranging from :

    • Mathematical modelling and simulation
    • Systems biology and bioinformatics
    • Software development
    • Systems biology and bioinformatics
    • Machine learning
    • High dimensional datasets processing and analysis
    • NGS data analysis
    • Multiomics and data integration
    • Mining genomic and clinical data
    • Development of algorithms to analyze genomics data
    • Drug discovery and safety assessment
    • Human genetics and pharmacogenomics
    • Precision medicine
    • e-medicine applications
    • Diagnosis

Education board

Pedagogic Committee 

    • Médéric Argentina (Institut de Physique de Nice, web page)

    • Pascal Barbry (Institut de Pharmacologie Moléculaire et Cellulaire, Nice, web page)

    • Florence Besse (Institut de Biologie Valrose, Nice, web page)

    • Frédéric Cazals (Institut de Recherche en Informatique et Automatique, Nice, web page)

    • Madalena Chaves (Institut de Recherche en Informatique et Automatique, Nice, web page)

    • Laurent Counillon (Laboratoire de PhysioMédecine moléculaire, Nice, web page)

    • Gaël Cristofari (Institut de Recherche sur le Cancer et le Vieillissement, Nice, web page)

    • Marcel Deckert (Centre Méditerranéen de Médecine Moléculaire, Nice, web page)

    • Fabienne De Graeve (Institut de Biologie Valrose, Nice, web page)

    • Arnaud Droit (Computational Biology Laboratory, Laval, Canada, web page)

    • Xavier Noblin (Institut de Physique de Nice, web page)

    • Agnès Paquet (Institut de Pharmacologie Moléculaire et Cellulaire, Nice, web page)

    • Jérémie Roux (Institut de Recherche sur le Cancer et le Vieillissement, Nice, web page)

    • Xavier Pennec (Institut de Recherche en Informatique et Automatique, Nice, web page)

    • Sophie Tartare-Deckert (Centre Méditerranéen de Médecine Moléculaire, Nice, web page)

Applications

Requirements

Students who apply to this program must be fluent in English (CECRL level B1) and have an established background in Mathematics, Physics or Computer Science for example, with a bachelor's degree or a license (French undergraduate degree) in a relevant field. 

Fees

The registration fee is 4000 euros per year for non EU students. Fees for French and EU students depend on the household income of the parents, from 300 to up to 4000 euros. Merit-based scholarships may exceptionally be allocated by the admission committee on the basis of the excellence of the student. Financial support may be provided for the internship's international mobility.

How to apply

  • The application process is available online APPLICATIONS ARE OPEN FOR 2020-2021!
  • Be prepared to upload documents such as a recent photo of yourself, a copy of your passport, your transcripts, your English proficiency certificate (Toefl or equivalent) if not native speaker, a resume (CV), a motivation letter, academic and/or professional reference letters
  • Let's start your online application,  (click on "E-application for IDEX international MSc. programs")
  • A detailed guide is available to help you in this application process

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Contact

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- Coordinator

(MSc  Project Manager)

 - Administrative - 

  (UCA student office coordinator)

 

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