Postdoc position: Data science and machine learning approaches for predictive modelling of disease...

Updated: 2 months ago
Job Type: FullTime
Deadline: 10 Jul 2021

As part of the euCanSHare H2020 project, we offer an exciting postdoctoral position at the Universitat de Barcelona, to develop data science and machine learning methods for predictive modelling of disease integrating imaging and non-imaging data. 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 candidates with a PhD in an area pertinent to the project and experience in mathematics/statistics, data science, machine learning, biomedical informatics, medical imaging, software development, and programming using C++/Python. The successful candidate is expected to be able to organise his/her work with minimal supervision and prioritise work to meet deadlines of the project. Due to multiple collaborations within the euCanSHare project with consortium partners from Europe and Canada, advanced oral and writing English knowledge are required.

Required skills:

- Machine/deep learning

- Predictive modelling

- Multi-source data integration

- 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 work independently, to lead on project deliverables and to co-supervise students

- Aptitude to collaborate with both technical and clinical collaborators

- Passion for applications of artificial intelligence in biomedicine and healthcare

The euCanSHare H2020 project is developing the first centralised, secure and sustainable platform for enhanced cross-border data sharing and multi-study personalised medicine research in cardiology. Initially populated with 35 European and Canadian cohorts (corresponding to over one million records), the platform will include extensive functionalities for data deposition, data harmonisation and data analysis. The features of the platform will be demonstrated and adjusted through several use cases, including for investigating diabetic cardiomyopathy, myocardial infarction and stroke using multi-factorial and multi-omics integrative approaches. The data analysis module of the platform will offer tools for cardiac image segmentation, cardiac quantification, and data quality control, as well as bioinformatics and machine learning capabilities.

The University of Barcelona (UB), founded in 1450, is one of the oldest universities in Spain. It comprises a student body of more than 84,000 and over 4,500 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 Barcelona Artificial Intelligence in Medicine Lab, which is an essential part of the Departament de Matemàtiques i Informàtica. BCN-AIM is composed of 16 full-time researchers in artificial intelligence, medical imaging, machine/deep learning, and health-related applications.

Acronym

euCanSHare

FBG project number

402143

Project title

An EU-Canada joint infrastructure for next-generation multi-Study Heart research

IP

Karim Lekadir

Department

Departament de Matemàtiques I Informàtica

Required documents

Motivation Letter, Curriculum Vitae

Send your application to:

email

isabell.tributsch@ub.edu

Name

Isabell Tributsch

email subject

Application – euCanSHare PostDoc

Gross salary per year

30,000 € - 40,000 € depending on experience


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