BONE STRENGTH is a public-private collaboration project funded by the Spanish Ministry of Science and Innovation (MICINN) and Agency of Research (AEI) that focusses on the prediction of fragile bone fractures in osteoporosis, out of routine clinical explorations. The collaboration will take place between the technology-based company 3D Shaper Medical SL, and the Barcelona Centre for New Medical Technologies (BCN MedTech) of the Universitat Pompeu Fabra (UPF). Both 3D Shaper Medical SL and UPF are in Barcelona, Spain.
Osteoporosis is a disease associated with the occurrence of fragile fractures in the elderly population, resulting in a huge burden on the society and the healthcare system. The current clinical gold standard for fracture risk assessment is based on areal bone mineral density (aBMD) measured using dual-energy X-ray absorptiometry (DXA) scan. However, it fails to identify up to 50% of the patients eligible for bone-specific pharmacological treatments, resulting in fractures that could be prevented. Bone strength, estimated using quantitative computed tomography (QCT)-based finite element analyses (FEA), has been shown to improve osteoporosis diagnosis and management. However, increased exposure of patients to X-ray radiations is a limitation in clinical practice. 3D-Shaper Medical SL has developed a software (3D-Shaper®) validated for predicting volumetric density and geometrical parameters of the proximal femur and lumbar vertebrae from planar DXA. It can provide clinicians with QCT equivalent parameters without performing a CT scan.
BONE STRENTH aims to develop a FEA module for 3D-Shaper® that will enable QCT-equivalent bone strength estimations from DXA scans. Through its Biomechanics and Mechanobiology Research Area (BMMB), BCN MedTech has a large experience in computational biomechanics and will develop the Finite Element methods that will be integrated into 3D-Shaper®. Bone strength calculations will be validated against experimentally measured values, and patient-specifically, against QCT-based FE predictions. Performance of the fracture risk assessment will be investigated using case-control clinical cohorts. Furthermore, the 3D-Shaper® FEA module will be used to evaluate the effect of pharmacological treatments, enabling clinical trials with a reduced economic cost and without performing CT scans.
Description of Work
BONE STRENGTH has two Principal investigators (PI). The PI at 3D Shaper Medical SL and coordinator of the project is Ludovic Humbert, Co-founder and CEO of 3D Shaper SL and expert in medical image processing and modelling in biomechanics. The PI at UPF is Jérôme Noailly, head of the BMMB at BCN MedTech, co-director of the SIMBIOSys group at the UPF Department of Information and Communication Technologies (DTIC), and expert in modelling and simulations in biomechanics and (systems) biology.
The successful Candidate will be a junior postdoctoral researcher, with proven experience in data science and computer simulations in biomedical engineering. He/She will be based at DTIC, UPF and will be responsible for osteoporosis patient stratification based on both clinical and biomechanical information, and for the development of a meta (surrogate) biomechanical model of the femur and the vertebra, to estimate bone strength at reduced computational cost, in collaboration with 3D Shaper Medical SL. Scientific and technical competencies are necessary in modelling and machine learning in biomechanics. Previous experience in physics-based computer simulations and bone biomechanics are welcome. The Researcher will collaborate with a small team of researchers dedicated to the same project and will report periodically to the respective PI of UPF and 3D Shaper Medical SL, to ensure (i) that the timelines of the project and deliverables are met, and (ii) that the project results can be properly disseminated through scientific and medical congresses and journals. Hence, communication, teamwork and leadership skills will be chiefly important.
At UPF, the successful Candidate will evolve in the highly international environment of DTIC. There, he/she will be able to interact directly with the 60+ investigators of BCN MedTech who gather expertise in medical image analysis and processing, machine learning and data science, complexity analysis, medical devices, and computational biomechanics and biology. Daily working interactions related to the project shall mostly happen with the teams of both the BMMB and the SIMBIOSys group. While day to day working language will be English, Spanish language fosters social interactions and (the learning thereof) is highly recommended.
The employment for BONE STRENGTH shall be for a period of up to 1,5 years. The successful candidate will be offered a full-time postdoctoral research contract for the implementation of BONE STRENGTH. The number of working hours is 37,5 h per week and 1640 h per year. The gross salary is 33.715,68 € per year. On top of this, social benefits (health, unemployment, retirement) are covered by the employer (UPF).
- Hold a BSc and a MSc in either Computer Science, Applied Mathematics, Physics, or any related field
- Have a PhD title, with a doctoral thesis focussed on Machine learning in biomedical engineering
- Be able to demonstrate a proficient level of English, both written and spoken. Language certificate is not mandatory but proper English level will have to be demonstrated during the interview (see selection criteria)
1st phase: remote pre-selection (0-100 points):
- The Scientific, Technological & Academic excellence will be considered, based on:
- A full CV that shall include, among others (0-70 points):
– A description of the current or, in case of unemployment, of the more recent position
Education and professional tracks
– Research experience supported by evidence such as: scientific publications; patents; participation in scientific congresses; participation in research projects including any leadership information; …
– International research collaborations
– International mobility experience (research stays longer than three weeks)
– Scientific mentoring activities: (co-)supervision of PhD, MSc and/or BSc theses; participation in scientific courses, workshops, summer or winter schools as instructor; …
– Roles in academia and/or in scientific societies
– Activities in science communication & outreach: press releases; online videos; participations to events for non-expert public; …
– Recognitions and merits: individual competitive grants; awards, invited talks, …
– A narrative biosketch with a section of the five major achievements of the CV
- Two reference letters provided by international scholars (0-15 points)
- Statement of purpose: past research experience; motivation to apply to this position; academic fit; contribution of the project to future careers plans; … (0-15 points)
To pass to the 2nd phase (see below), the Candidate must have scored at least 75/100 during the remote review.
IMPORTANT: the publication records will be double checked through online databases (Web of Science, Scopus, Google Scholar, ResearchGate, ORCID, …). The Candidate is encouraged to provide the link of his/her choice in the CV. Failure to access to any online database of the scientific production of the researcher will justify the exclusion of Applicant from the selection process.
2nd phase: interview(s) (0-100):
Should the Applicant be preselected during the 1st phase, (s)he will be informed by email, for a 2nd phase of selection. The 2nd phase will consist in at least one interview through which:
- the English language (eliminatory if deemed insufficient),
- the motivation (0-15 points),
- the proactive behaviour (0-15 points),
- the capacity to work collaboratively (0-15 points),
- the organizational skills (0-15 points),
- the communication skills (0-15 points), and
- the capacity to engage in a scientific discussion and manage problems (0-15 points),
will be assessed, among other aspects (0-10 points will be reserved for the general impression).
The interview must lead to a score of at least 75/100, so that the Candidate can be considered for the final decision.
The final decision will be the result of a consensus made by the Recruitment Committee that will consider the results of both selection phases 1 and 2. The Applicant will be informed of the selection outcome by email.
IMPORTANT: The referees might be contacted by the Recruitment Committee, to reach the final decision.