The Data Science for Health (DSH) Research Unit focuses on the design, the development and the implementation of predictive models for the life sciences. In particular, statistical machine learning and deep learning algorithms are applied to integrated health data such as Electronic Health Records (EHR), different levels of -omics data and bioimages of diverse nature, from CT, PET, MRI scan to Digital Pathology WSIs. The aim is to create novel mathematical methods and ICT platforms connecting physiopathological patterns of disease with high dimensional data now available for Functional Genomics (e.g DNA microarrays, SNPs, proteomics, Deep Sequencing), with clinical and imaging data and geodatabases of environmental factors and socio-demographic data.
FBK actively seeks diversity and inclusion in the workplace and is also committed to promoting gender equality.
The candidate will work in the scope of the projects of the DSH Unit, with the role of Junior Software Developer. This role requires a basic knowledge of the fundamental elements of the machine learning theory for imaging and omics data, with a particular emphasis on mastering deep neural networks, both theoretically and practically, aimed at the construction of end-to-end pipelines to be run on different computational facilities.
Typical tasks will include:
- supporting the Senior researchers in the design, optimization, implementation and running predictive machine learning models, both shallow and deep, on local GPU, distributed clusters and cloud facilities;
- supporting the Senior researchers in the planning phases of the model design;
- supporting the Senior researchers in the results dissemination activities, at different levels (e.g. website maintenance, paper writing).
The ideal candidate should have:
- Good knowledge of the Python language and its data science libraries (scikit-learn)
- Good knowledge of the PyTorch interface for deep learning
- Basic experience in working with imaging/bioimaging data
- Basic knowledge of the Tensorflow and Keras interface for deep learning
- Basic knowledge of the basic concepts of machine learning and deep learning
- Good knowledge of the Django framework
- Good knowledge of the HTML/CSS suite
- Good knowledge of written and spoken English (at least B1-B2)
- Teamwork attitude
- Good communication and relational skills
- Basic knowledge of the R programming language
- Experience with Docker and PostgreSQL
Type of contract: Fixed term contract
Working hours: part-time (14 h per week)
Start date: January 2022
Duration: 12 months
Gross annual salary: about 9.350 €
Workplace: Povo, Trento (Italy).
Benefits: flexi-time, company subsidized cafeteria or meal vouchers, internal car park, welcome office support for visa formalities, accommodation etc., supplementary pension and health found, training courses, public transport, sports facilities, language courses fees. Further details at www.welfarefbk.info.
Interested candidates are requested to submit their application by completing the online form (https://jobs.fbk.eu/). Please make sure that your application contains the following attachment (in pdf format):
Application deadline: 29th November, 2021
Please read our Recruitment Regulations before completing your application.
For further information, please contact the Human Resources Services at email@example.com.