3-year research engineer (IGR) in Statistics and Machine Learning (funded by Amidex)

RESEARCHER PROFILE: Postdoc / R2: PhD holders 

RESEARCH FIELD(S)1: Mathematics

MAIN SUB RESEARCH FIELD OR DISCIPLINES1: Statistics

JOB /OFFER DESCRIPTION: Applications are invited for a three-year full time research engineer position starting in September-October 2025 in the A*MIDEX Chaire d'Excellence-funded project “Nonstationary Models of Biological Signals” (NOMOS), Principal Investigator Prof. Anna Dudek.  According to the requirements of this funding program, candidates should not be currently employed by the University of Aix-Marseille and should have obtained their last degree outside AMU. Interviews with candidates will be conducted in English.

Project NOMOS Overview

Nonstationary signals are at the forefront of modern statistical analysis, as many observed phenomena cannot be adequately modeled by stationary processes. The NOMOS project aims to develop a new generation of nonstationary models and algorithms for analyzing various biological signals. The project will focus mainly on developing innovative models for biomedical signals with irregular cyclicity and exploring potential machine learning applications.

Engagement: 

50% of time dedicated to team collaboration, including statistical simulations, and research tasks such as developing and optimizing algorithms, testing and validating models, and conducting literature reviews, preparing presentations. Responsibilities also include writing and debugging codes for statistical modeling and machine learning applications, as well as documenting methodologies and results.

50% of time focused on consulting for researchers at Aix-Marseille University and collaborating on applied projects with other laboratories. Tasks include data preparation and cleaning, designing and implementing machine learning workflows, performing statistical analyses, creating visualizations and dashboards, presenting findings to researchers, and contributing to research papers, reports, and grant proposals.

TYPE OF CONTRACT: TEMPORARY / JOB STATUS: FULL TIME                 

APPLICATION DEADLINE: 30/05/2025 16:00 GMT+1

ENVISAGED STARTING DATE: 01/09/2025

ENVISAGED DURATION: 32 months

WORK LOCATION(S): Institut de Mathématiques de Marseille (I2M, UMR 7373), 3 place Victor Hugo Case 19 13331 Marseille Cedex 3 

WHAT WE OFFER: Salary according to the scale

Additional information: The Euraxess Center of Aix-Marseille Université informs foreign visiting professors, researchers, postdoc and PhD candidates about the administrative steps to be undertaken prior to arrival at AMU and the various practical formalities to be completed once in France: visas and entry requirements, insurance, help finding accommodation, support in opening a bank account, etc. More information on AMU EURAXESS Portal 

QUALIFICATIONS, REQUIRED RESEARCH FIELDS, REQUIRED EDUCATION LEVEL, PROFESSIONAL SKILLS, OTHER RESEARCH REQUIREMENTS 

Profile: strong background in statistics and machine learning methods (PhD in statistics or machine learning), experience in statistical consulting welcomed, very good skills in R and/or Python, good knowledge of statistical learning methods. Up to 5 years of experience after PhD. Duration: 32 months. Full time. 

NOMOS is committed to promoting diversity and gender equality. Our selection process is based solely on merit, free from bias or stereotypes. We strongly encourage women to apply, and our recruitment efforts actively promote female participation. We will closely monitor gender balance to ensure equal opportunities for all selected candidates.

Soft skills: Ability to work in a team, high communication skills, excellent ability to organize work, very good knowledge of English.

REQUESTED DOCUMENTS OF APPLICATION, ELIGIBILITY CRITERIA, SELECTION PROCESS

Applicants should include the following materials in their application: 

• their full academic CV, including a list of publications,
• a cover letter (max 1 page), 
• two reference letters to be sent directly by the referees to [email protected]

HOW TO APPLY: [email protected]