Bioinformatics and Machine learning with cell-free systems

Type de poste
Niveau d'étude minimal
Dates
Durée du poste
Contrat renouvelable
Contrat renouvelable
Date de prise de fonction
Date de fin de validité de l'annonce
Localisation
Nom de la structure d'accueil
Adresse

Domaine de Vilvert
78352 Jouy-en-Josas
France

Contacts
Jean-Loup Faulon
Email du/des contacts
jean-loup.faulon@inra.fr
Description

We are seeking a candidate to develop machine learning tools to mine metabolic pathway data acquired on cell-free systems. The successful candidate will take part in synthetic biology projects funded by the French funding research agency (ANR) and the EU (H2020) at the MICALIS Institute.

MICALIS (INRA & AgroParisTech, Jouy-en-Josas) is a research unit of more than 350 researchers developing multidisciplinary approaches and promoting microbial systems biology towards the development of synthetic biology applications for health and biotechnology. Within MICALIS, the recruiting research team (http://www.jfaulon.com) specializes in developing whole-cell and cell-free synthetic biology for pathway and biosensor engineering to produce biologically active molecules and monitor disease biomarkers.

The person recruited is expected to develop: (i) state-of-the-art supervised machine learning tools to predict activities of engineered metabolic pathways, and (ii) a reinforcement/active learning pipeline to propose novel pathway sequences for cell-free synthesis and experimental characterization. These tasks will be performed using training sets built from experimental data already obtained by the host laboratory. The person recruited will also benefit from several years of experience the research team has in developing machine learning for systems & synthetic biology [2]. The position will necessitate interactions with molecular biologists. The persons recruited will closely collaborate with an IT research engineer, a postdoctoral appointee working on synthetic biology workflow developments, and wet laboratory research scientists already accustom to work together.

Applicant’s profile:
- Applicants should have a master, engineering, or a Ph.D. degree in either: systems & synthetic biology, molecular biology, computational biology, or computer science with a working knowledge of biology.
- Ability to write high-quality research manuscripts, strong collaborative skills, and excellent communication skills in English are required.
- Experience with machine learning open source tools is anticipated

The position is opened for 12 months (renewable) from July 1st, 2019. The appointee will be hired through fixed-term contracts in accordance with the French legislation. Salary will be commensurate with qualifications and experience.

To Apply: Applicants should send a detailed curriculum vitae, a letter of intent explaining their motivations for the position, and contact details of two references. Send your applications to: jean-loup.faulon[at]inra.fr.

[1] Delépine B, et al. RetroPath2.0: A retrosynthesis workflow for metabolic engineers. Metabolic Engineering, 45: 158-170, 2018. Duigou T, et al. Nucleic Acids Research, 47(D1): D1229-1235, 2019. See also: http://www.jfaulon.com/bioretrosynth/
[2] Mellor J, et al. Semi-supervised Gaussian Process for automated enzyme search. ACS Synthetic Biology, 5(6): 518-528, 2016. See also: http://www.jfaulon.com/machine-learning-methods-for-biotechnology-appli…

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