RESEARCH FIELDEngineeringMathematicsPsychological sciences
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE04/02/2020 19:00 - Europe/Athens
LOCATIONSpain › Barcelona
TYPE OF CONTRACTTemporary
HOURS PER WEEK40
“LA CAIXA” DOCTORATE INPHINIT
35 PhD fellowships for early-stage researchers of any nationality to pursue their PhD studies in research centres accredited with the Spanish Seal of Excellence Severo Ochoa, María de Maeztu or Health Institute Carlos III. This frame is addressed exclusively to PhD research projects on STEM disciplines: life sciences and health, experimental sciences, physics, chemistry and mathematics.
D-Risc capitalizes on previous research at BCN MedTech, to assess the risk of disc degeneration (DD). Patient-specific IVD finite element (FE) models will be coupled to agent-based (AB)/network cell models, to predict catabolic shifts of cell activity in function of morphological, metabolic and mechanical factors. According to subsequent machine learning analyses, specific combination of factors will be identified as possible risks for DD.
Low back pain (LBP) affects up to 85% of people at some point in life. It is strongly related to DD, with phenotypes that cannot be explained solely by genetic factors as they also depend on mechanical loads.
In vivo or in-vitro studies investigated DD at the cell and tissue levels, but they are costly and limited in terms of parameterization, effective number of measurements and long-term observations. In contrast, computational modelling allows testing different boundary conditions (mechanical, biochemical, …) and numerous theoretical hypotheses over long timescales, at a relatively limited cost.
Coupled to personalized organ models, multiscale models and simulations can indicate common patterns in specific groups of IVD, as well as critical combinations of cell stimuli and the effects thereof on DD observable features. In particular, the mining of model inputs together with simulated data can reveal such patterns and combinations.
The successful candidate will join the BCN MedTech team and will be co-supervised by faculties, experts in computational multiscale modelling and machine learning. (S)He will systematically analyze the 3D anatomy of 500 patient-specific IVD FE models, available at UPF, to define relevant groups of FE /AB multiscale simulations. Then, (s)he will use machine learning algorithms to build correlation models among personalized model inputs and predicted cell activity, to create a DD risk score model.
D-Risc will involve key collaborations with population cohort infrastructures in UK and Finland.
Area of knowledge
Physical Sciences, Mathematics and Engineering
Group of disciplines
Telecommunications, Electronics, Robotics, Biomedical Engineering, Automation Engineering, ICT
Biomedical Engineering, ICT
Research project / Research Group description:
Research project and main focus of the research line of the research group in which the fellow would join
D-Risc aims to reveal critical interplays of crucial stimuli within the intervertebral disc (IVD) that might lead to IVD degeneration, based on morphological and physiological parameters. Different models at the organ, tissue and cellular levels will be used. Specifically, the project will combine multi-physics finite element models at the organ and tissue levels with agent-based and network models at the cell and molecular levels, to simulate the local regulation of IVD cells in multifactorial physical and biochemical micro-environments. Simulation results will be mined with patient-specific morphological, physical activity and life-style data. Depending on the identified multiscale paths that can lead to degeneration-related cell activity (i.e. catabolic shift of cell activity), personalised recommendations for prevention- and optimised conservative treatments will be established.
D-Risc will exploit the competencies of the Biomechanics and Mechanobiology (BMMB - http://biomech.es) lab of the BCN MedTech research unit at the Department of Information and Communication Technologies (DTIC) of the Universitat Pompeu Fabra (UPF), Barcelona. The project will be additionally implemented in cooperation with the medical image analysis and machine learning areas of BCN MedTech (http://bcn-medtech.upf.edu/).
UPF was established in 1990 as a public university with strong dedication to excellence in research and teaching. It is the 1st Spanish university in the world Top 200 (THE2020), the 11th (ranked 5th in Europe and 1st in Spain) under 50 years (THE18). It also ranked 5th in Europe and 1st in Spain (U-Multirank 2018) in teaching and research performance (U-Ranking, BBVA Foundation & Ivie, 2018), quality output (excellence rate), normalized impact and percentage of collaborative papers with foreign institutions. UPF is full member of the Big Data Value Association (BDVA). DTIC has since its creation emphasized scientific excellence and internationalisation as core aspects of its activities. It has an important track record of active participation in EU projects (a total of 66 FP7 projects and 10 other projects in non-FP7 program such as CIP, Ambient Assisted Living and the Lifelong Learning Program, and, up to now 44 H2020 projects). It is the Spanish university department with the largest number of ERC grants (9 FP7 and 9 H2020) and is part of the FET Flagship initiative “The Human Brain Project”. DTIC has been awarded the “María de Maeztu” excellence by the Spanish government for the quality and relevance of its pioneering scientific research.
BCN MedTech is the Barcelona Centre for New Medical Technologies at UPF. It focusses on biomedical integrative research, including mathematical and computational models, algorithms and systems for computer-aided diagnosis and treatment, and the translation thereof into relevant clinical problems and industrial products. It has a team of 60 full time researchers working on medical image and signal processing, computational simulation, computer-assisted surgery and biomedical electronics. Within BCN MedTech, the BMMB lab combines mechanistic and stochastic theoretical modelling with computational methods in biology and physics, to rationally explore the complex multiscale interactions between tissue multiphysics and biological processes, and to understand the bottom-up regulation of the functional biomechanics of organs in health and disease. The specific targets are cartilaginous (rheumatic disorders), bone (osteoporosis), arterial (atherosclerosis) and lung (emphysema) tissues. The project will combine this expertise with computational anatomy and manifold learning techniques for patient stratification, from the BCN MedTech medical image analysis and machine learning areas.
The maximum total payment amount will be €122,592, as broken down below:
· Three annual payments of €34,800 each one. Where applicable, the amounts corresponding to the Social Security contributions payable by the employer (in this case, the host institution), as well as any other compulsory fee, whether current or that may be provided for in a future legal framework, will be deducted from the yearly gross amount of €34,800 to be received by the fellow.
· €3,564 per year, as an additional amount for conferences, courses, research stays, consumables, equipment, charges for the use of intellectual property, etc. This additional amount will be managed by the centre for the benefit of the fellow and must be justified separately.
· ”la Caixa” Banking Foundation will award a prize of €7,500, which will be paid in the fourth year, should the fellow be able to deposit their thesis within 6 months after the third year of their fellowship has ended.
· ”la Caixa” Banking Foundation will sign an agreement with the host institution, which will receive the fellowship payment directly. This must be wholly allocated to cover the amounts arising from Social Security contributions and other required corporate expenses payable by the employer, where applicable, as well as the fellow’s gross stipend and the additional amount.
· Experience: At the call deadline, applicants must be in the first four years (full-time equivalent research experience) of their research careers and not yet have been awarded a doctoral degree.
· Studies pursued: At the time of recruitment, candidates must comply with one of the following options:
o To have completed the studies that lead to an official university degree adapted to the European Higher Education Area awarding 300 ECTS credits, of which at least 60 ECTS credits must correspond to master level.
o To have completed a degree in a university not adapted to the European Higher Education Area that gives access to doctoral studies. The verification of an equivalent level of studies to the ones mentioned above will be made by the university when the admission procedure starts.
· Geographic mobility: For candidates applying to Spanish centres or units: Candidates must not have resided or have carried out their main activity (work, studies, etc.) in Spain for more than 12 months in the 3 years immediately prior to the call deadline.
· Level of English: Candidates must have a demonstrable level of English (B2 or higher).
Deadline: 4 February 2020
18 February 2020 - Deadline for submitting the language certificate.
16 April 2020 - Notification of the shortlist results.
27 and 28 May 2020 - Face-to-face interviews in Barcelona.
2 June 2020 - Publication of the final list of selected candidates.
From 2 to 30 June 2020 - Matching research centre – fellow.
Dr Jérôme Noailly
Barcelona Centre for New Medical Technologies (BCN MedTech)
Department of Information and Communication Technologies
Universitat Pompeu Fabra, Barcelona, Spain
Press articles related with the work of the BCN MedTech BMMB team in disc degeneration:
Required Research Experiences
YEARS OF RESEARCH EXPERIENCE1 - 4
REQUIRED EDUCATION LEVELOther: Master Degree or equivalent
REQUIRED LANGUAGESENGLISH: Good
EURAXESS offer ID: 464411
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