Open PhD positions

Two fully funded PhD positions on Recommender Systems are available at the RecSys Lab at Politecnico di Miano, Italyin the following topics  

  • Applied Quantum Machine Learning 
  • Evaluation of Recommender Systems 

Possible intakes are May 1st or November 1st, 2020.  Application deadline for the first intake is March 13rd at 14:00.

Each Ph.D. student will have access to additional funds to participate in conferences, summer schools and other Ph.D. related expenses.  Monthly net salary is € 1400 for 3 years. Scholarships are sponsored by ContentWise 



Prospective candidates are highly encouraged to contact prof. Paolo Cremonesi ( or Maurizio Ferrari Dacrema ( a preliminary interview before submitting the official application. 

Both positions have title “UX personalization for innovative digital media services“. When submitting your “Research proposal” (“Elaborato progetto di ricerca”), please describe if your are interested to work on “Applied Quantum Machine Learning” or “Evaluation of Recommender Systems”.



The successful candidates are expected to pursue a Ph.D. in Information Technology and to conduct highly competitive research in the field of Recommender Systems. The selected candidates will be working together with several Ph.D. students and senior researchers. 

We expect applicants to have strong analytical, problem solving, and software experience as well as good knowledge in many of the following areas: 

  • Recommender Systems 
  • Machine Learning from a practical as well as a theoretical perspective
  • Development and evaluation of predictive models 
  • Implementation of algorithms in Python and other languages 
  • Optimization 
  • Significance testing 

Depending on the topic, we also expect candidates to have further knowledge and experience in: 

(for the position on Quantum Machine Learning for Recommender Systems)

  • Operations research 
  • Linear algebra 
  • Describing and solving NP-complete and NP-hard problems 

(for the position on Evaluation of Recommender System algorithms) 

  • Neural networks (Recurrent NNs, Convolutional NNs) 
  • Deep learning 

Applicants must hold a Master degree (or equivalent) in computer engineering or computer science, and should have an excellent track record, maturity, self-motivation, as well as the ability to work both independently and in an interdisciplinary team. Experience in scientific projects, international cooperation and publication activities are considered an asset. Candidates should have very good command of the Italian or English languages.