Gesucht: Programmierer*in

Gesucht: Eine motivierte Programmiererin bzw. ein motivierter Programmierer für Redesign und
Neuimplementierung einer in die Jahre gekommenen Anwendung mit der Eiszeiten (genauer die
Auslastung von Eisflächen) und die Anzahl von Teilnehmer*innen erfassen und ausgewertet werden.

Bei Interesse bitte mit Peter Schartner (peter [dot] schartner [at] aau [dot] at) Kontakt aufnehmen.

PhD Students in Cybersecurity wanted!

The Cybersecurity Research Group – hosted at the university’s Digital Age Research Center (D!ARC) – is seeking to fill the post of a Phd-student within the area of Side Channel Resistent Embedded Systems.

The Cybersecurity Research group has been established with a clear interest in finding and eliminating information leaks in the context of embedded devices (they often exhibit a number of so called side channels). In this particular setting, the research team – led by Prof. Elisabeth Oswald – has developed a range of techniques that integrate well in a typical software flow and make leakage information transparent to a developer.

Currently, the group consists of one further lecturer, three postdocs, and two further PhD students who work in the areas of cryptography, statistical machine learning, embedded security, artificial intelligence and deep learning as well as crypto engineering.

The purpose of this studentship is to build on the existing work and add novel ideas including the automated tracing of leaks from lower-level code representations to the description in a higher-level language, the development of code transformation techniques to mitigate leaks automatically, etc. The successful applicant will work closely with Prof. Oswald and will develop into a researcher/engineer with a profound understanding of the challenges of leakage resilient development.

Requirements:

✓ Master’s level qualification in informatics, mathematics or other technical sciences
✓ strong background in embedded systems
✓ some background in low level programming and embedded systems
✓ Very good language skills in English (German optional)
✓ Willingness to work within an international team

The vacancy shall be filled as soon as possible.
If you are interested in this opportunity please consider applying with your CV and a motivational letter to elisabeth [dot] oswald [at] aau [dot] at

Master in Artificial Intelligence and Cybersecurity

Interested in the future of technology? Then this jointly-run MSc programme might be the perfect fit for you! The universities of Klagenfurt and Udine collaborate to offer this highly focused program on the core subjects of Artificial Intelligence and Cybersecurity with an additional emphasis on the social, ethical and legal aspects that arise in practice.

The MSc in Artificial Intelligence and Cybersecurity is a two-year taught programme. It consists of three semesters of taught courses followed by a research project leading to the submission of a thesis and its defence at the end of the fourth term.

Over 50 students from all around the globe registered in the premiere of this MSc in October 2020 (all lectures were held online). The hands-on classes, the profound theoretical inputs as well as the multidisciplinary approaches were the major cornerstones making this first semester a huge success.

The application for the summer semester of 2021 is now open and students who are interested in this MSc will find more information here:

https://www.aau.at/en/studien/master-artificial-intelligence-and-cybersecurity/

Master Thesis: “Predictive Analytics for Price and Demand Forecasting”

Modern business enterprises are facing complex market, resource and workforce management requirements, involving highly differentiated and dynamic processes, supply chains and demands. Artificial Intelligence (AI) technologies from the fields of Data Mining, Machine Learning and Recommender Systems are getting more and more pervasive to support strategic planning and decision making. The goal of this Master thesis is to perform a systematic investigation of major application areas and key AI technologies constituting the state of the art in predictive analytics for price and demand forecasting in energy, producing and service industries.

The Master thesis topic is suitable for students of Information Management or Applied Informatics. Depending on the specific focus the Master thesis takes, the supervision will be coordinated between:

  • Univ.-Prof. Dr. Martin Gebser
  • Univ.-Prof. Dipl.-Ing. Dr. Dietmar Jannach
  • Assoc.-Prof. Dipl.-Ing. Dr. Erich Christian Teppan
  • Postdoc-Ass. Dr. Christian Wankmüller

For further information, please contact Univ.-Prof. Dr. Martin Gebser (Martin [dot] Gebser [at] aau [dot] at), research group for Production Systems.

 

The following are some (incomprehensive) literature references, which can be consulted as a starting point for going more in depth or broadness while the Master thesis evolves:

  • P. Schwarenthorer, A. Taudes, J. Hunschofsky, C. Magnet, M. Tschandl: Increased Company Performance through Macroeconomics Sales Forecasting: A Case Study. Journal of Japanese Operations Management and Strategy 10(1): 1-17, 2020
  • M. Seyedan, F. Mafakheri: Predictive Big Data Analytics for Supply Chain Demand Forecasting: Methods, Applications, and Research Opportunities. Journal of Big Data 7: Article 53, 2020
  • B. Wu, L. Wang, S. Lv, Y. Zeng: Effective Crude Oil Price Forecasting using New Text-based and Big-Data-driven Model. Measurement 168: Article 108468, 2021
  • N. Ludwig, S. Feuerriegel, D. Neumann: Putting Big Data Analytics to Work: Feature Selection for Forecasting Electricity Prices using the LASSO and Random Forests. Journal of Decision Systems 24(1): 19-36, 2015