Hello,
A full professor position is open at the Laboratoire de Biométrie et Biologie Évolutive (LBBE, UMR CNRS 5558, Université Lyon 1), in models, algorithms and machine learning in bioinformatics and genomics.
The application deadline is June 3rd, 4pm CEST, and the starting date will be at the end of 2021.
Feel free to quickly get in touch with the research and teaching contact if you think you may be interested.
Best regards,
Laurent
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TEACHING :
The recruited person will be primarily involved in the bioinformatics master, which she will contribute to steer and to
further develop, so as to adapt to recent and ongoing progress on the front of digital sciences and the use of big-data in
biology. She/He will also be implicated in the undergraduate and graduate programs in biological sciences, ecology and
health that are supervised by the targeted educational team (Biometry and Evolutionary Biology, BBE). In this context,
she/he will give courses in mathematics, statistics, modeling, machine learning and artificial intelligence, such as applied
to bioinformatics and genomics. She/He will also be involed in the global strategic thinking on the general question of
how to best develop multi-discplinary and research-based teaching programs on the front of Digital Sciences for Biology
and Health, such as formalized in the context of the currently developing SFRI networking project at the level of the
University of Lyon, in partnership with the mathematics and computer sciences departments of the University. Of note,
some of the courses (in particular undergraduate programs) will have to be given in French (within two years after
recruitment).
Teaching contact :
Céline BROCHIER, Professor,
celine....@univ-lyon1.fr , tel 04 26 23 44 76
RESEARCH :
The recruited person will develop a research project in bioinformatics, statistical, evolutionary or functional genomics,
with a strong theoretical and methodological component, in relation with stochastic modeling and data analysis in
bioinformatics, evolutionary, molecular or cellular biology. In terms of biological applications, the research activity may
pertain to a broad range of themes, aiming to take advantage of genomic and multi-omic data to model the processes
underlying the evolution of species, their genomes, their phenotypes and reproductive modes, or the temporal dynamics
and the functional integration of biodiversity. The methodological approaches may pertain to: methods, algorithms and
stochastic models applied to multi-omics; machine learning, AI and deep learning applied to the analysis of molecular
and functional data; models and methods in population genetics, evolutionary or statistical genomics.
Research contact :