Phd Student, Combidiag Marie-curie Fellowship - Huningue, France - FIRALIS GROUP

FIRALIS GROUP

Entreprise vérifiée

Huningue, France

il y a 4 semaines

Posté par:

Sophie Dupont

beBee Recruiter

Description

CombiDiag is funded under the Horizon Europe - Marie Skłodowska-Curie Actions - Doctoral Network (H2020-MSCA-DN) designed to promote movement of researchers in Europe and for this reason,
is open to researchers from any country in the world provided they have not carried out their main activity (work, studies, etc.) in France for more than 12 months in total within the previous 3 years preceding the date of recruitment.

The Research Programme

The PhD fellowship at Firalis S.A., in co-supervision with the University of Côte d'Azur

Genetic, genomics, epigenetics via targeted and global NGS
Proteomics with soluble markers measured by Olinks, multiplex, multianalyte technologies
Lipidomics and metabolomics by mass spectrometry platforms.

APPLICATION PROCESS

Application deadline
28th February 2023

Contact person
Hélène SCHLIER
Head of Human Resources
17, rue du Fort
68330 HUNINGUE, FRANCE

Tel:

BENEFITS

Fellows shall be appointed with an employment contract limited to 36 months.

GENERAL Requirements

ESSENTIAL QUALIFICATIONS_

Master degree in one of the following data science domain: mathematics, statistics, data minding, physics, bio-informatics, modelling, deep learning...

PREFERRED QUALIFICATIONS/EXPERIENCES_
Research or medical experience in molecular biology, biomarker researches, and/or neurosciences
Very good communication and presentation skills
Experience in common data science, data statistics, data mining techniques and relevant software packages (e.g., R/Python ) used for the analysis of biological data
Learning statisticsbased evaluations and evidences via integrative data analysis, using different modelling and AI tools
Maintains overall awareness in the field of biostatistics by reading related literature, attending training classes, attending professional meetings, etc.
Experience in handling large data sets (e.g., from sequencing, proteomics, imaging, Mass Spectrometry)
Knowledge of coding languages and software such as R and Python, GitHub know

- how and use of html-based tools for reporting