Three-year PhD position in Modeling human homeostatic capability: Multivariate analysis of cardiorespiratory and metabolic exercise tests for health assessment (Funded by Amidex)
27 Mar 2024
Job Information
- Organisation/Company
Aix-Marseille Université- Research Field
Computer science » Programming
Computer science » Other
Engineering » Control engineering
Engineering » Other- Researcher Profile
First Stage Researcher (R1)- Country
France- Application Deadline
1 Sep 2024 - 21:59 (UTC)- Type of Contract
Temporary- Job Status
Full-time- Hours Per Week
38- Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme- Is the Job related to staff position within a Research Infrastructure?
No
Offer Description
RESEARCHER PROFILE: PhD/ R1: First stage Researcher
RESEARCH FIELD(S)1: Computer Science
MAIN SUB RESEARCH FIELD OR DISCIPLINES1: Medicine
JOB /OFFER DESCRIPTION
Context and Positioning
Homeostasis is the process by which living organisms maintain a stable internal balance necessary for their survival and optimal functioning. This process typically involves feedback mechanisms that detect deviations from a target state and activate responses to correct these deviations and return the system to a stable level. The homeostasis capabilities of an individual are used to support medical decision making, such as patients’ peri-operative risk stratification in lung cancer surgery.
The homeostatic abilities of an individual can be assessed through exercise testing, which is the traditional clinical method for evaluating patients' health status and overall systemic dynamics. A series of tests is designed to measure features representative of the individual's homeostatic capabilities, with one significant metric being the maximal oxygen uptake (VO2max). These measurements are obtained through routine functional tests and maximal exercise sessions, aimed at challenging the entire organism to evaluate physiological adaptive responses. When exercise performance or maximal aerobic capacity is limited for a given patient, the medical doctor has to identify the failing physiological function and to provide a coherent system failure mechanics analyzing the monitored data. However, medical doctors still analyze the collected physiological data in a univariate approach as historically developed. Currently, in the research community, the human body is considered as a dynamic physiological complex system. Recently, the framework of network physiology was proposed, giving a central role to homeostasis.
To broaden theoretical knowledge and to fill the gap between current research and medical practice, the Exercise Test Laboratory of Hôpitaux Universitaires de Marseille built its own activity database composed of 2500 exercise tests.
Objectives
This thesis aims at exploiting this dataset in order to provide a global understanding and interpretation framework of the multivariate data generated during maximal exercise testing to improve patients’ homeostasis phenotyping through their homeostatic capabilities.
We aim to develop a medically and statistically consistent approach to identifying and quantifying determinants of overall performance as well as aerobic performance from monitored variables. This would provide physicians with improved analytical tools to achieve a more relevant and precise patient exercise phenotyping.
The thesis project aims to go further and provide physicians with a quantitative decision support indicator. It will be developed by focusing on the dynamic interactions between the recorded variables. Here, we consider in particular adapting the framework of physiological networks to the mesoscopic and macroscopic case of exercise tests. This would provide crucial information to the physician about patients' homeostatic capacities.
Work environment
The recruited candidate will work at LIS-lab and C2VN, in Marseille. They will have access to the computing cluster of LIS Lab.
In addition to the supervising team, the PhD candidate will work in close collaboration with a junior hospital doctor.
The complete offer is available here:
https://www.lis-lab.fr/wp-content/uploads/2024/03/Sujet_these_homeostasie-2.pdf
TYPE OF CONTRACT: TEMPORARY / JOB STATUS: FULL TIME / HOURS PER WEEK 35
APPLICATION DEADLINE: 01/09/2024
ENVISAGED STARTING DATE: September 2024
ENVISAGED DURATION: 36 months
JOB NOT FUNDED THROUGH AN EU RESEARCH FRAMEWORK PROGRAMME
WORK LOCATION(S): Laboratoire d’Informatique et des Systèmes, LIS Lab, Aix Marseille Université, Campus de Saint Jérôme , Bat. Polytech, 52 Av. Escadrille Normandie Niemen 13013 Marseille, France/ Centre de Recherche en Cardiovasculaire et Nutrition, C2VN Lab, Aix-Marseille Université - Campus Santé Timone - Faculté de Médecine, 27 Bd Jean Moulin, 13005 Marseille, France
WHAT WE OFFER:
A three-year PhD contract with the following salary:
2024: 2 100 € per month before tax
2025: 2 200 € per month before tax
From 2026 and onward: 2 300 € per month before tax
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 (years of research experience (max. 3000 characters)
We are looking for a candidate with a Masters level degree in one of the following:
- System and control theory
- Signal/Image/Graph processing
- Computer science
- Machine learning/Artificial intelligence
Good coding skills are also required, preferably in Python
The candidate should have both an appeal to work on precise and effective medical problems, and a strong theoretical background.
Soft skills: Autonomy, Teamwork, Critical thinking, especially when interpreting results
REQUESTED DOCUMENTS OF APPLICATION, ELIGIBILITY CRITERIA, SELECTION PROCESS
- CV
- Motivation Letter
- Master’s degree transcript
HOW TO APPLY: please send the requested documents to: [email protected]
Requirements
- Research Field
- Computer science
- Years of Research Experience
- 1 - 4
- Research Field
- Computer science
- Years of Research Experience
- 1 - 4
- Research Field
- Engineering
- Years of Research Experience
- 1 - 4
- Research Field
- Engineering
- Years of Research Experience
- 1 - 4
Additional Information
- Website for additional job details
https://academicpositions.com
Work Location(s)
- Number of offers available
- 1
- Company/Institute
- Aix-Marseille Université
- Country
- France
- City
- Marseille
- Postal Code
- 13284
- Street
- Jardin du Pharo 58, bd Charles Livon
Where to apply
- Website
https://academicpositions.com/ad/aix-marseille-universite/2024/three-year-phd-p…
Contact
- City
Marseille- Website
https://www.univ-amu.fr/- Postal Code
13284
STATUS: EXPIRED