ORGANISATION/COMPANYUniversitat de Barcelona
RESEARCH FIELDComputer scienceMathematics
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE21/02/2020 00:00 - Europe/Athens
LOCATIONSpain › Barcelona
TYPE OF CONTRACTTemporary
HOURS PER WEEK37,5
OFFER STARTING DATE15/03/2020
EU RESEARCH FRAMEWORK PROGRAMMEH2020
As part of the EarlyCause H2020 project, we offer an exciting PhD student position at the Universitat de Barcelona and its DataScience@UB centre, to develop algorithms and tools for predictive modelling of individual-specific health and disease trajectories using multi-factorial approaches, integrating biological, environmental and clinical determinants.
Precisely you will be joining the Barcelona Artificial Intelligence in Medicine LAb (BCN-AIM), a young and dynamic research group, aiming to enhance medical care through big data-enabled AI.
We are seeking a candidate with a Msc degree (or equivalent) in an area pertinent to the project, such as applied mathematics, advanced statistics, machine learning, data science, programming using C++/Python, and/or biomedical informatics. We are looking for highly motivated candidates with strong interests in mathematical and computational applications in biomedicine. Candidates must have excellent teamwork and communication skills, and be enthusiastic about their research. Due to multiple collaborations within the EarlyCause project with consortium partners from Europe, advanced oral and writing English knowledge are required. Female applicants are explicitly encouraged to apply.
The EarlyCause H2020 project will leverage a unique collection of birth cohorts, longitudinal data and experimental models to identify causative mechanisms linking early life adversity (in children and pregnant women) to multi-morbidity development. Concretely, the project will focus on depression and two of its main physical comorbidities, namely coronary heart disease and diabetes. The consortium will disentangle the complex biological contributions from four key interconnected domains linked to ELS, namely epigenetics, inflammation, neuroendocrine system, and microbiome. Furthermore, modifying effects of environmental factors such as sex/gender, socioeconomics, lifestyle and behaviour will be quantified, thus uncovering potential intervention targets that may reverse the causative mechanisms and reduce the impact of ELS on multi-morbidity development in high-risk individuals.
To achieve the goals of the project, this highly multi-disciplinary and experienced consortium will combine state-of-the-art and novel approaches from basic, pre-clinical and clinical research, including advanced statistical and mathematical methods, animal models of prenatal and postnatal stress, cellular models in various tissues, and integrative bioinformatics and machine learning methods. The consortium members will also enable access and exploitation of the largest set of European cohorts, comprising rich information on early stressors, biological and omics data, as well as depressive, cardiovascular and metabolic clinical outcomes.
The University of Barcelona (UB), founded in 1450, is one of the oldest universities in Spain. It comprises a student body of 84,370 and 4,548 research staff members. With 73 undergraduate programs, 273 graduate programs and 48 doctorate programs, UB is the largest university in Barcelona and Catalonia. The UB is ranked the first Spanish university according to several rankings (QS World University Rankings 2018, ARWU/Shanghai Ranking 2018). It is particularly interested in fostering international relations and, for many years, has managed an average of 150 European projects per year. Since January 2010, Universitat de Barcelona is part of the prestigious League of European Universities Research (LERU). The research will be carried within the DataScience@UB research section, which is an essential part of the Departament de Matemàtiques i Informàtica. DataScience@UB is composed of 15 highly experienced academics in artificial intelligence, computer vision, medical imaging, machine/deep learning, and health-related applications.
FBG project number
Causative mechanisms and integrative models linking early-life-stress to psycho-cardio-metabolic multi-morbidity
Departament de Matemàtiques I Informàtica
Gross salary per year
Application letter, Curriculum vitae, etc.
Send your application to:
Application – EarlyCause PhD
- MSc or equivalent in computing, mathematics, statistics, applied mathematics, biomedical engineering, or equivalent
- First selection based on CV and letter
- Interviews by a panel of academics from the University of Barcelona (via skype or in person)
- Possible invitation to on-site interview with a short presentation
REQUIRED EDUCATION LEVELComputer science: Master Degree or equivalentMathematics: Master Degree or equivalent
REQUIRED LANGUAGESENGLISH: Excellent
- Machine/deep learning
- Predictive modelling
- Applied mathematics
- Error / uncertainty estimation
- Biomedical informatics
- Excellent programming skills in Python and/or C++
- Excellent English, both oral and written
- Good team spirit and participation to the scientific life of the lab
- Aptitude to collaborate with both technical and clinical collaborators
- Passion for applications of artificial intelligence to biomedicine
- High motivated for research
EURAXESS offer ID: 484426
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