StudMa: CiRiEngine

Student Employee for Machine Learning Project in Tour Recommender Systems | 20 hours per week | 6 months

The Technical University of Vienna, Austria’s premier institution for research and education in engineering and natural sciences, has contributed significantly to Austria’s research landscape for over 200 years. Embracing the motto “Technology for people,” TU Wien fosters innovation through its 26,000 students and more than 4,000 scientists.

In the Research Unit of Data Science, within a FFG-funded project, a collaboration between CityRiddler GmbH and TU Wien, we are seeking a Student Employee starting April 2024 for 20 hours weekly. This position is limited to 6 months with the possibility of extension but only up to the completion of the master’s or diploma degree.

Your tasks:

• Assist in evaluating and selecting machine learning algorithms for tour recommendation optimization, including Naïve Bayes, Linear SVM, Logistic Regression, and cutting-edge methods like POIBert.
• Support dataset preparation and preprocessing, using open data sources and partner APIs for geolocation and tour data.
• Help in implementing, training, and optimizing the machine learning model with our team’s guidance.
• Address technical challenges such as data quality assessment, algorithm performance evaluation, and prevention of model overfitting, using established techniques.
• Contribute to administrative tasks and participate in project-related meetings.
• Write a master thesis based on this work and contribute to potential publications.

Your profile:

• Demonstrates a passion for working in an academic environment.
• Background in Data Science or Business Informatics.
• Currently enrolled in a relevant study program at TU Wien, without having completed a master’s or diploma degree.
• Exhibits commitment, reflective ability, and a capacity for learning.
• Ready for teamwork and cooperation, with strong communication skills, empathy, and enjoyment in interacting with others.

We offer:

• A dynamic and varied role within a supportive team.
• Hybrid working arrangements, with up to 60% home office option.
• Access to a broad range of attractive social benefits, as outlined in TU Wien’s fringe benefit catalog.
• Extensive internal and external training opportunities and various career paths.
• A central location with excellent accessibility (U1 Taubstummengasse).

Interested candidates should send their motivation letter, CV, and transcripts/grades in PDF format to recsys-lab[ät]ec.tuwien.ac.at by February 20, 2024 (Subject: “StudMa: CiRiEngine”)

We look forward to your application!