Data Science Postdoctoral Researcher for Machine Learning Based Disease Prediction from Large-Scale...

As part of the LongITools H2020 project, we offer an exciting data science postdoctoral position at the Universitat de Barcelona and its Artificial Intelligence in Medicine Lab (BCN-AIM). The selected researcher will develop algorithms and tools for predictive modelling of individual-specific health and disease trajectories using multi-factorial approaches, integrating biological, environmental and clinical predictors. This position offers the opportunity to take part in the emerging fields of both biomedical artificial intelligence and the human exposome.

We are thus seeking candidates with a PhD and expertise in an area pertinent to the project and experience in machine learning, biomedical informatics, bioinformatics, advanced statistics, digital health and/or programming.

Candidates must have excellent teamwork and communication skills, be enthusiastic about their research, and have creative problem-solving skills. The successful candidate is expected to be able to organise their work with minimal supervision, prioritise tasks to meet project deadlines, and represent the lab at meetings. Due to continual collaboration with LongITools consortium partners from across Europe, advanced oral and writing English knowledge are required.

The LongITools H2020 project will leverage a unique collection of birth cohorts data, other types of longitudinal data, and clinical registers to characterise longitudinal trajectories of environmental exposure and cardio-metabolic health and disease. A key objective will be to generate evidence-based predictions which can ultimately translate into innovative healthcare applications for individualised health monitoring, risk assessment, and disease prevention. The LongITools project will also allow researchers and policymakers to generate new knowledge for identifying the likely direct and indirect causal mechanisms through which exposures to human-made environmental factors affect the risk of cardio-metabolic disease.

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 2020, ARWU/Shanghai Ranking 2020). 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, the University of Barcelona is part of the prestigious League of European Universities Research (LERU).

The candidate with join the Artificial Intelligence in Medicine Lab (www.bcn-aim.org ), which is an integral part of the University of Barcelona’s Faculty of Mathematics and Computer Science. It is a young and dynamic research lab, highly active in international projects, and composed of 18 enthusiastic academics, researchers, students and research managers, with expertise in data science, machine/deep learning, biomedical informatics, biomedical ethics, and health-related applications.

Acronym

LONGITOOLS

FBG project number

402164

Project title

Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases

IP

Karim Lekadir

Department

Departament de Matemàtiques I Informàtica

Gross salary per year

€32,00 - 40,000, depending on experience

Required documents

Application letter, Curriculum vitae, etc.

Send your application to:

email

[email protected]

Name

Catherine Gallin

email subject

Application – LongITools Data Science Postdoc