The Bruno Kessler Foundation (FBK) conducts research activities in Information Technology, Materials and Microsystems, Theoretical Physics, Mathematics, Italian-Germanic historical studies, Religious studies and International Relations. Through its network, it also develops research in the fields of international relationships, conflict causes and effects, European economic institutions, behavioral economics and evaluative assessment of public policies.
The Digital Health & Wellbeing Center is one of the Centers of the Bruno Kessler Foundation (FBK). The activities of the Center for Digital Health & Wellbeing mainly concern scientific research of excellence in the field of Computer Science and AI techniques and methodologies for health and healthcare, as well as social and technological innovation for a relevant impact on both the local community and nationally and internationally.
The candidate will use statistical machine learning algorithms, both shallow and deep, to develop, optimize, implement, apply, and validate predictive models for the life science, – in particular in the health domain. Training data will consist of EHRs, PGHD, different levels of omics data, biomedical images and digital pathology WSIs provided by the collaborating labs. Particular attention will be devoted to the reproducibility of the methodology, the interpretability of the algorithm(s), the data integration and the translatability of the models into clinical support tools.
● Identify and discuss with the partners the diagnostic/prognostic tasks.
● Organize, clean, and prepare the provided data.
● Follow all the steps of a learning pipeline using the available data to tackle the task of
● Implement and validate the solution on a computational infrastructure.
● Discuss the solution with the collaborating partners.
● Disseminate the findings on scientific papers and talks.
● Help supervising B.Sc, M.Sc. and Ph.D. students.
● Help writing grants and projects.
● Help manage research projects.
The Ideal Candidate shall have:
● PhD Degree in Mathematics, Physics, or related fields.
● Research experience in the field of Statistics, Machine Learning, both supervised and
unsupervised, deep learning and Mathematical Modeling.
● Solid knowledge in bioimages processing and experience in medical data preprocessing
and cleaning, including neural data, CT/PET scans, MRI scans, histology data, omics data, electronic health records, electronic case report forms
● Research experience in model implementation in Python, in-depth knowledge of the
PyTorch, or Tensorflow and Keras interfaces for deep learning would be a plus; –
● Established publication record in international peer-reviewed journals and established
record of poster/oral presentations in international conferences.
● Time management,planning, and development skills. Accuracy, flexibility, proactivity, and goal orientation.
● Teamwork approach, good communication and relational skills.
● Ability to build graphical interfaces and knowledge of the basics of data visualization.
● Knowledge of model implementation on HPC solutions and basic knowledge of the R
language and of the Matlab framework.
Gross annual salary: about 41.400,00 €, plus objectives achievement bonus.