PhD position - Data science and machine learning techniques for predictive modelling of health and...

Updated: about 2 months ago
Job Type: FullTime
Deadline: 20 Sep 2020

As part of the EarlyCauseH2020 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 asapplied mathematics, advanced statistics, machine learning, data science, programming using C++/Python, and/or biomedical informatics. We are looking for highly motivated candidateswith 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 EarlyCauseH2020 project will leverage a unique collection of birth cohorts, longitudinal data and experimental models toidentify 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 willdisentangle 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 assex/gender, socioeconomics, lifestyle and behaviour will be quantified, thus uncovering potential intervention targets that mayreverse 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-artand 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 integrativebioinformatics and machine learning methods. The consortium members will also enable access and exploitation of thelargest set of European cohorts, comprising rich information on early stressors, biological and omics data, as well asdepressive, 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

402 158

Project title

Causative mechanisms and integrative models linking early-life-stress to psycho-cardio-metabolic multi-morbidity


Karim Lekadir


Departament de Matemàtiques I Informàtica

Gross salary per year


Required documents

MotivationLetter, Curriculum Vitae

Send your application to:



Katharina Heil

email subject

Application – EarlyCausePhD

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