Doctoral Fellowship in Business Analytics and Recommender systems

Offer description

Research topic :

We seek applications for a full-time four-year PhD student position in the field of Recommender Systems. Nowadays, the large amount of information available often creates a cognitive overload when it comes to decision making. Recommender systems are becoming more and more popular to help users navigate through the world of possible choices.
There are two common and recurrent challenges when designing a recommender system. First, the “ramp-up” or “cold- start” problem, that is, when the model has to face a lack of information when new users or new items enter the system. Second, the presence of a popularity bias, when systems generate recommendations biased towards more popular items. Consequently, users acting on those suggestions are amplifying even further the sources of bias in the system.
The thesis focuses on exploring creative ways to solve sparcity and bias issues by deriving features from unstructured data sources (e.g., social media and digital activities).

Research environment :

You will belong to the Louvain Research Institute in Management and Organizations (LouRIM). The institute is devoted to theoretical and applied, empirical and experimental studies of management of private and public organizations, including but not limited to research on internal and external functional management processes that are present in all enterprises and organizations. Your research might involve other academic or industry partners.

What to include in your application:

• a motivation letter, including full contact details
• a curriculum vitae (with relevant grades)
• ideal starting date (optional, if different from 1st September 2022)

Additional Information

Benefits

The PhD position has a duration of 4 years. The candidate starts with a two-year contract and will be extended to four years after a positive evaluation

Selection process

Step 1 : candidates send their application before the mentioned deadline (September 30st, 2022)
Step 2 : short-listed candidates will be invited for an interview. The candidates who are not selected will be notified in writing.
Step 3 : short-listed candidates will be ranked based on their interviews. If the top ranked candidate fits the position, they will be offered the position. Other candidates will be notified in writing.

Skills/Qualifications

Required skills

• Master degree in Business Engineering, Computer Science, Management, Applied Mathematics, Statistics or equivalent. good oral and written english skills
• Programming skills (e.g., python or R)
• Competences in statistical and/or mathematical modeling
• Teamwork, effective communication and creativity

Preferred skills

• Previous research experience
• Previous experience with recommender systems
• Previous experience with machine learning