PhD student Position at UPF in Barcelona (Interactive machine learning in online professional networks)

We have an opening for an PhD Candidate within the research topic of interactive machine learning in online professional networks. This position is part of the industrial PhD program and the research project will be developed in a company in collaboration with the university. The position is for three years.
The present project will be conducted within the company Fluttr (www.fluttr.in) and the Department of Information and Communication Technologies (http://www.ai.upf.edu/). Fluttr is a professional network that focuses on people's interests, talents and passions. Members join one or multiple communities of interests (i.e. design, CEO community, startups community, developers community, etc.) with the objective to discuss, learn and discover the best professional like-minded or complementary people, events and opportunities. The core objective of Fluttr is to change the current recruitment market. While the job market is rapidly changing mainly due to technology advancements, the recruitment market has not followed suit and the CV (created in the XV century) still represents the first fundamental milestone in the hiring process.
Research project description: One of the main technological challenges in our society is how to make sense of the unprecedented volumes of data that are continuously generated in order to guide and support decision making. An important limitation of the current approaches to deal with is the lack of a learning process that can (1) obtain and evaluate feedback of the system’s performance from the environment and (2) adapt accordingly to improve the future performance. This is the basis Reinforcement learning (RL), the area of machine learning concerned with learning to control a system (or agent) that interacts with an environment so as to maximize a performance measure that expresses a long-term objective. What distinguishes reinforcement learning from other machine learning paradigms is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the system.
Fluttr generates and uses large amounts of complex data from different sources that is used to build matches to create professional opportunities. Examples of matches are between members of a same community or different ones, between members and available jobs, provide pro-active recommendations for local events, training courses and products (for example books) that might be of interest to each member.
The present project proposal addresses the challenges faced by the recommendation engine of Fluttr. The first objective is to collect and study behavioral patterns and user profiles to extract knowledge and create a first predictive model. The model is going to form the basis of the learning systems developed in the following objectives:
- Integrating recommended matches (actions) in the predictive model and analyzing how these action spaces with different structures (e.g., actions organised in a graph) and different levels of interaction between actions (e.g., similarity between actions) may influence the learning performance.
- Developing efficient algorithms that work in non-stationary environments when not only the performance of each action evolves, but also the structure of the action space can change over time.
Your Profile: We are looking for highly motivated, talented and enthusiastic candidates with an active attitude and excellent communication and collaborative skills. The successful applicant has completed a master degree in data science or related field. The candidate is expected to understand contemporary topics and issues in Data Science. For example, multivariate statistics, machine learning, data mining and algorithmic complexity. An interview will be part of the selection procedure.
Information and application: Questions regarding this positions can be directed to Vicenç Gómez or Gergely Neu . To apply for this position, please subscribe to the open call in this website before February 15th, 2017:
http://doctoratsindustrials.gencat.cat/en/projects...