Post-doc position: machine learning for large-scale microscopy images analysis

Posted Dec 6, 2016

We are looking for a highly motivated postdoctoral Research Fellow to join us in a successful collaboration with the European Laboratory for Non-linear Spectroscopy (LENS) to apply machine learning methods for the quantitative analysis of large-scale microscopy data (see e.g. Frasconi et al. 2014, Silvestri et al. 2015).

Job description

The successful candidate will be employed for at least 18 months in the field of machine learning applied to the extraction of quantitative neuroanatomical information from the microscopy images. They are expected to work in a multidisciplinary environment in tight collaboration with LENS, within the framework of the Human Brain Project. In particular, they are expected to conceive, develop and deploy robust algorithms for fully-automated segmentation and classification of blood vessels, neuronal cells, and neuronal processes (dendrites/axons). Such novel algorithms can either extend the recent approaches based on semantic deconvolution or can be based on completely novel approaches.


  • Ph.D. in computer science or closely related disciplines;
  • Significant expertize in development of new algorithms for
  • biomedical image analysis and/or machine learning;
  • Excellent programming skills, preferably in Python, C/C++ or Java;
  • Ability to carry out an independent research program;
  • Oral and written proficiency in English and the open mindset needed to work in a multidisciplinary international environment.


  • Type of contract: Fixed Term Contract (Assegno di ricerca)
  • Gross annual salary: about 30.500 Euro
  • Working hours: full time
  • Workplace: Firenze (DINFO and LENS)


Candidates are required to send their application by email to Prof. Paolo Frasconi. The application must include:

  • Detailed CV with a list of publications
  • Statement of research interests
  • Email addresses of at least two academic references

Review of applications will begin immediately and will continue until the position is filled. Candidates who pass the initial CV screening will be contacted for interview (which may be done via Skype).