PhD Fellowship in DC 8 – Mechano-chemo models of the knee and intervertebral disc joints, to explore the emergence of age-related risk factors of degeneration

Description

This PhD project will focus on coupling biological regulatory network and organ finite element models to define risk factors of different rates or organ ageing in personalised models related with patient (osteoarthritis, low back pain) and population cohorts, with which UPF works. The objectives are: 1) Couple pre-existing models at UPF: chondrocyte and intervertebral disc mechano-sensitive cell regulatory networks models with finite element models of the knee joint and the intervertebral disc; 2) Personalise the shapes of the organ models by combining magnetic resonance image segmentation and mesh morphing; 3) Personalise the regulatory network initial states, based on patient BMI, age and other factors known to control low grade inflammation mediators mapped in the networks; 4) Run simulations and mine together input data for model personalization and simulated data related with network node activations that reflect nociceptive pain, pro-inflammatory cytokine activity, balance between matrix proteases and inhibitors thereof, structural proteins; 5) Define a pipeline for model assessment, based on uncertainty and consistency analyses, falsification tests against clinical cases, capacity for discrimination in clinical case-control: 6) Assess risk factors and build corresponding surrogate models.
A successful project will result in a robust pipeline for multiscale modelling that allows mechanistic explorations of pathophysiological mechanisms and risk factor predictions for age-related joint degeneration, based on interpretable biological mechanisms.

The candidate will benefit of a salary approximately € 31,000 to € 36,000 per annum (depending on family status). She/he will conduct research in recognized international teams and will attend all the common training events of the Network (PhD schools, workshops, and convened sessions at international conferences).

Qualifications

Candidate's profile:

• You hold both a Bachelor’s and a Master’s degree in Biomedical Engineering, Biomedicine, Computer Science, Industrial Engineering, Mechanical Engineering.
• Specialization in computational methods in biomedical engineering or biomedicine will be highly beneficial.
• You have a keen interest in the fields of in silico medicine, digital health, and rheumatology.
• You have proven your proficiency in English language equivalent to B2 level (Sufficient English level will be verified during the interview, if any).
• You did not reside or carry out your main activity (work, studies, etc.) in the host institution's country for more than 12 months in the three years before 1st of January 2025.
• You are ambitious, well organized, a team player, and have excellent communication skills.
• You can work independently and have a critical and analytical mindset.
• You are a pro-active and motivated person, eager to participate in network-wide training events, international mobility, and public dissemination activities.
• Previous experience in finite element modelling, and/or medical image processing, and/or data science, and/or motion capture and analyses, are not required but considered a plus.

Application Instructions

Application requirements:

• Curriculum vitae.
• Motivation Letter, including a clear indication of the preferred DC position(s) within InSilicoHealth Doctoral Network if the applicant postulates for multiple positions.
• Academic records (grades) of both the Bachelor’s and Master’s degrees.
• Two recommendation letters by two previous scientific supervisors (these people might be contacted by the Evaluation Committee of the position, if needed).

Equal Employment Opportunity Statement

UPF promotes a diverse and inclusive environment and welcomes applicants regardless of age, disability, gender, nationality, race, religion or sexual orientation.