Management, Machine Learning and Statistical Methods

1 Research Collaborator position
(Deadline July 31st, 2020 12:00 )
Fields

Management, Machine Learning, Financial Distress, Credit Risk Management, Credit Behavior, Zombie Firms

Activity
The successful candidate will contribute to develop academic research to be published in international peer reviewed journals focusing on firms' financial distress and crisis, credit risk management, business performance, zombie firms, credit behavior and cost behavior. Responsibilities of the successful candidate will include project management activities, literature scoping, data collection and analysis, writing of peer-reviewed publications.
The research projects will engage a wide gamut of methodological approaches with a strong focus on quantitative techniques, including statistical data analysis and machine learning. The knowledge of management themes, business analytics and machine learning are equally important to carry out the research activities.
Experience in collecting and analyzing financial and historical companies’ data is preferential.
In this role, the successful candidate will be responsible for delivering excellent academic research outputs, to be submitted and published in international peer reviewed journals.
Profile
The IMT School for Advanced Studies in Lucca invites applications for a Research Collaborator in Management, Machine Learning and Statistical Methods.
The candidate must have a background in management, with experience in the themes of firms' financial distress and crisis, credit risk management, business performances, zombie firms, credit behavior and cost behavior.
The candidate must also have a strong background in quantitative methods and machine learning, with the ability to apply such techniques to real economic and business problems. The knowledge of management themes, business analytics, and machine learning are equally important to carry out the research activities
Formal requirements
  • A Ph.D. in Business and Management, Physics, Engineering, Mathematics, Statistics or related fields;
  • A record of publications in peer reviewed journals in Management science;
  • Experience in quantitative data analytics techniques;
  • An excellent command of written and spoken English.
Specific requirements
  • The candidate must have the professional background to work in a highly collaborative and multidisciplinary team;
  •  Interdisciplinary articles in the fields of financial distress, credit risk management, firms’ crisis, zombie firms, credit behavior and cost behavior are welcome.
Project

Regional Business Clusters as economic polymers: mathematical modelling, forecasting, and optimal policy design (EcoPoly)

Duration

1 year, renewable

Gross amount

Approx. 20350€/year

Job Research Unit: 
AXES
Job Contract Type: 
Assegno di ricerca

Application

Apply ONLINE only.

Guidelines for applying through the PICA platform (Italian | English).
Before filling in the application form, please read thoroughly the full call and collect all the files you may need:

Info

  • Personal info and contact info (compulsory);
  • University degree (compulsory);
  • PhD (compulsory only if stated in the full call).

Attachments

  • The scanned copy of a valid identity document (Passport or Identity Card - compulsory);
  • Your CV in English (compulsory).