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    • Specialty – Bioinformatics and Artificial Intelligence (BIX)

    Over the past two decades, bio­in­for­ma­tics has become a cen­tral dis­ci­pline of the life sciences, at the inter­face of bio­lo­gy, gene­tics, com­pu­ter science and data science. High-through­put sequen­cing now pro­duces bio­lo­gi­cal data on an unpre­ce­den­ted scale, and its ana­ly­sis relies more and more on advan­ced com­pu­ta­tio­nal methods and arti­fi­cial intel­li­gence. The pro­gramme trains bio­in­for­ma­tics spe­cia­lists with strong com­pu­ta­tio­nal and AI exper­tise, who can turn large-scale geno­mic and mole­cu­lar data into actio­nable know­ledge for pre­ci­sion medi­cine, sus­tai­nable agri­cul­ture, food secu­ri­ty and biotechnology.

    Can­di­da­ter

    Guide des UE

    Pedagogy

    • Geno­mics and gene­tics are the scien­ti­fic core of the programme.
    • Arti­fi­cial intel­li­gence, high-per­for­mance com­pu­ting, sta­tis­ti­cal model­ling and soft­ware engi­nee­ring pro­vide the methods to work at scale.
    • Genomes, regu­la­to­ry net­works, mole­cu­lar path­ways and popu­la­tions are trea­ted as com­plex, high-dimen­sio­nal and mul­ti-scale systems.
    • The pro­gramme is open to life-science gra­duates and to gra­duates in com­pu­ter science, data science, mathe­ma­tics or engineering.
    • Stu­dents learn to build methods, not only to use exis­ting tools. They pro­gram in Python, R and Java and work in Linux and on HPC infrastructure.
    • Stu­dents ana­lyse real short- and long-read sequen­cing data, from qua­li­ty control to de novo genome assembly.
    • Tea­ching is in English, with lec­tures from resear­chers at lea­ding ins­ti­tu­tions in Europe and the Uni­ted States.

    Professional objectives

    Gra­duates work as bio­in­for­ma­tics engi­neers and scien­tists in research labo­ra­to­ries, R&D teams and indus­try. Their sec­tors include geno­mics and gene­tics, pre­ci­sion medi­cine and health data science, agri-food and crop geno­mics, food qua­li­ty and safe­ty, and bio­tech­no­lo­gy and phar­ma­ceu­ti­cal R&D.

    They can also go on to a PhD in bio­in­for­ma­tics or com­pu­ta­tio­nal bio­lo­gy. They can ana­lyse high-through­put geno­mic data inde­pen­dent­ly, apply machine lear­ning to bio­lo­gi­cal data, and desi­gn robust bio­in­for­ma­tics software.

    Contact and documentation

    Res­pon­sable mas­ter
    San­drine Moran­dat
     +33 (0)3 44 23 44 23
    Res­pon­sable du par­cours
    Fady Moha­reb
     +33 (0)3 44 23 43 53

    Guide de l'étudiant

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