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Annonce

2 avril 2019

Opening of a PhD position in Molecular Data Analysis and Machine Learning


Catégorie : Doctorant


A PhD position of 3 years duration is opened on molecular imaging analysis and machine learning within the framework of a cross-disciplinary collaboration between LBBE lab, Hospices Civils de Lyon, and the Imagine team, LIRIS lab at Ecole Centrale de Lyon.

Visit here for full information: https://docs.google.com/document/d/10akDJe9X6i0W2ZiM8OHebxnoD2WssCaHpnxls0I3O0o/edit?usp=sharing

 

GeoMx Digital Space Profiling is a cutting-edge molecular imaging technology used in biology to quantify gene expression in situ at very high-plex. Spatially-resolved data are mapped back onto the tissue allowing deep analysis of interactions between cell types, impact of position, etc. Lyon University Hospital was granted the Centre of Excellence for the development of clinical tests using this innovative approach. First projects are encompassing fields of interest as diverse as prediction of response to anti-cancer drugs, molecular mechanisms of graft rejection or predictive signature of Parkinson disease.

The analytical challenge is multiple. Using a gridded profiling, the research work will focus first on pattern recognition in spatial RNA count in order to map molecular parameters to tissue architecture and decipher the role of spatial distribution of biomarkers independently. Machine learning approaches will be compared to smooth penalised modelling. Second, the work program will deal with the correlation of the different biomarkers map in order to confirm or raise hypotheses regarding tissue mechanisms. Third, working on longitudinal samples, the biomarkers map evolution will be studied to identify trajectories of tissue evolution either prognostic and/or predictive for treatment response.

Within this project, one of the task is to provide a toolset to fully exploit the spatial information contained in this new type of data.

We are seeking a highly motivated intern student (from Master or Engineering Schools) in the field of computer sciences, more specifically applied to machine learning, and interested in interface with human health. .

Skills

The candidate should have programming skills (Python, C/C++, R), ideally already applied to machine learning, as well as biostatistics fundamentals. Fluency in either French or English is required.

Environment

The successful candidate will work in direct collaboration with researchers having an established expertise in computer vision and machine learning (Liris laboratory UMR CNRS 5205) in partnership with Lyon University Hospital Biostatistics and Genomics core facility (Pr D. Maucort-Boulch, PhD supervisor and Dr J. Lopez). Ecole Centrale de Lyon is part of the top ten engineering schools in France (Grande Ecoles), part of the elite of "Grande Ecoles" offering access to excellent quality graduate and undergraduate students.

Application

Applications should include a detailed curriculum vitae, report card, brief statements of interests and two reference letters.

Applications and letters should be sent via electronic mail to:

Dr Jonathan LOPEZ

Responsable médical de la Plateforme BIOGENET Sud - Hospices Civils de Lyon

Service de Biochimie et Biologie moléculaire – Centre Hospitalier Lyon Sud

Faculté de Médecine Lyon Sud - Université Lyon 1

Centre de Recherche en Cancérologie de Lyon - INSERM U1052 CNRS U5286

jonathan.lopez@univ-lyon1.fr

0478861607 / 0783566895

 

     

Pr Delphine Maucort-Boulch

Service de Biostatistique-Bioinformatique des HCL,

Chef de service

Pôle de Santé Publique, chef de pôle

Centre Hospitalier Lyon-Sud

Bâtiment 4D, secteur Sainte Eugénie

165 chemin du Grand Revoyet

69495 Pierre-Benite Cedex France

secrétariat : 00 33(0) 4 78 86 57 75/ 13 26

Tel : 33 (0) 4 78 86 57 64

Fax : +33 (0) 4 78 86 57 74

delphine.maucort-boulch@chu-lyon.fr

www.chu-lyon.fr

 

MD, PhD

 

Site Lacassagne

Bâtiment A

162 Avenue Lacassagne

69424 Lyon Cedex 03 FRANCE

Tel : 33 (0) 4 72 11 57 36

Fax : 33 (0) 4 72 11 51 41

http://mastersantepublique.univ-lyon1.fr

 

UMR 5558 CNRS UCBL

Département Biostatistiques et modélisation pour la santé et l’environnement

Equipe Biostatistique Sante

 

* Pr. Liming Chen (lchen@ec-lyon.fr)

 

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