Thema für eine Bachelor- oder Masterarbeit: Dark Pattern against Privacy

“Dark Patterns” sind manipulative Designstrategien auf Webseiten oder Apps, die Nutzer dazu bringen, unerwünschte Handlungen auszuführen, wie z.B. mehr Daten preiszugeben oder unerwünschte Abonnements abzuschließen. In diesem Projekt sollen Dark Patterns speziell im Hinblick auf Datenschutz klassifiziert und bestehende Taxonomien angepasst werden, um ihren Einfluss auf den Datenschutz besser zu verstehen. Zusätzlich wird die Verbreitung solcher Praktiken in Österreich untersucht und eine erste rechtliche Einschätzung zu deren Compliance mit Datenschutzgesetzen vorgenommen.

Bei Interesse melden Sie sich bitte bei Frau Jasmin Wachter (jasmin [dot] wachter [at] aau [dot] at)!

Trends in Recommendations Systems – A Netflix Perspective

Thursday April 7th 2022 | 05.30 pm (CET) | via Zoom

Anuj Shah, Ph. D. | Senior Machine Learning Research Practitioner at Netflix |

Click here to register for the meeting:

https://zoom.us/meeting/register/tJYvdO-gqzMiEtKOfNIgcZAZOQ8jA3i_b3Pi

 

Abstract:

Recommendation systems today are widely used across many applications such as in multimedia content platforms, social networks, and ecommerce, to provide suggestions to users that are most likely to fulfill their needs, thereby improving the user experience. Academic research, to date, largely focuses on the performance of recommendation models in terms of ranking quality or accuracy measures, which often don’t directly translate into improvements in the real-world. In this talk, we present some of the most interesting challenges that we face in the personalization efforts at Netflix. The goal of this talk is to sunshine challenging research problems in industrial recommendation systems and start a conversation about exciting areas of future research.

 

Bio:

Anuj Shah is a Senior Machine Learning Research Practitioner at Netflix. For the past 10+ years, he’s been working on an applied research team focused on developing the next generation of algorithms used to generate the Netflix homepage through machine learning, ranking, recommendation, and large-scale software engineering. He is extremely passionate about algorithms and technologies that help improve the Netflix customer experience with highly personalized consumer-facing products like the Continue Watching row, the Top 10 rows amongst many others. Prior to Netflix, he worked on machine learning in the Computational Sciences Division at the Pacific Northwest National Laboratory focusing on technologies at the intersection of proteomics, bioinformatics and Computer Science for 8 years. He has a Ph.D. from the Computer Science department at Washington State University and a Masters in C.S. from Virginia Tech

Senior Scientist without PhD (all genders welcome)

This is a non-binding translation of an official job announcement (in German) that can be found here.

The University of Klagenfurt, with approximately 1,500 employees and over 12,000 students, is located in the Alps-Adriatic region and consistently achieves excellent placements in rankings. The motto “per aspera ad astra” underscores our firm commitment to the pursuit of excellence in all activities in research, teaching and university management. The principles of equality, diversity, health, sustainability and compatibility of work and family life serve as the foundation for our work at the university.

The University of Klagenfurt is pleased to announce the following open position at the Department
of Artificial Intelligence and Cybersecurity at the Faculty of Technical Sciences, employment to commence as soon as possible:

Senior Scientist without PhD (all genders welcome)

Level of employment: 75 % (30 hours/week)

Minimum salary: € 31.200,40 per annum (gross); classification according to collective agreement: B1

Limited the duration of a maternity leave

Application deadline: December 8, 2021

Reference code: 708/21

Tasks and Responsibilities:

  • Participation in research and teaching activities of the Information Systems research group
  • Engaged collaboration in administrative and organizational tasks of the department
  • Participation in public relations activities of the department or the faculty

In research and teaching, the Information Systems research group works on the application of AI-based intelligent systems to practical operational problems. The research group focuses in particular on the design and evaluation of recommendation systems, the application of data mining methods in business environments and personalized software services in general. The spectrum of the research activities ranges from the application of new methods of artificial intelligence to research into the effects of such information systems on their users. The Department of Artificial Intelligence and Cybersecurity is very well networked internationally in science and industry.

Prerequisites for the appointment:

  • Completed relevant master’s or diploma studies at a university in Austria or abroad
  • Proven knowledge in computer science, especially in programming
  • Fluent knowledge of German and English in spoken and written form or willingness to acquire them within the first year of employment

Additional desired qualifications:

  • Relevant international and practical work experience
  • Social and communicative competences and ability to work in a team
  • Project experience
  • Fundamental experience with university teaching and research activities
  • Didactic experience
  • First relevant publication(s) (apart from the Master’s or diploma thesis)

Our offer:

The employment contract stipulates a starting salary of € 2.228,60 gross per month (14 times a year;
previous experience deemed relevant to the job can be recognised in accordance with the collective
agreement).

The University of Klagenfurt also offers:

  • Personal and professional advanced training courses, management and career coaching
  • Numerous attractive additional benefits, see also https://jobs.aau.at/en/the-university-as-employer/
  • Diversity- and family-friendly university culture
  • The opportunity to live and work in the attractive Alps-Adriatic region with a wide range of leisure activities in the spheres of culture, nature and sports

The application:

If you are interested in this position, please apply in German or English providing the usual
documents:

  • Letter of application
  • Curriculum vitae
  • Certificates and support letters

To apply, please select the position with the reference code 708/21 in the category “Scientific Staff” using the link “Apply for this position” in the job portal at jobs.aau.at/en/.

Candidates must furnish proof that they meet the required qualifications by December 8, 2021 at
the latest.

For further information on this specific vacancy, please contact Dietmar Jannach (Dietmar [dot] Jannach [at] aau [dot] at). General information about the university as an employer can be found at https://jobs.aau.at/en/the-university-as-employer/. At the University of Klagenfurt, recruitment and staff matters are accompanied not only by the authority responsible for the recruitment procedure but also by the Equal Opportunities Working Group and, if necessary, by the Representative for Disabled Persons.

The University of Klagenfurt aims to increase the proportion of women and therefore specifically invites qualified women to apply for the position. Where the qualification is equivalent, women will be given preferential consideration.

People with disabilities or chronic diseases, who fulfil the requirements, are particularly encouraged
to apply.

Travel and accommodation costs incurred during the application process will not be refunded.

Applied Data Science – Use Cases and Challenges in the Semiconductor Industry

Dr. Anja Zernig | KAI Kompetenzzentrum Automobil- und Industrieelektronik GmbH Villach |
Friday, November 26, 2021 | 10:00 (CET, 09:00 UTC) | S.1.42

Online: https://classroom.aau.at/b/sch-xte-ijl-jdg

 

Abstract: AI has infected the world. Today, there is a huge hype around Data Science activities all over the world, where one of the biggest challenges for the industry is to deliver financial value quickly but also sustainably. In her talk, she will show some examples on latest Use Cases in the area of Data Science within the semiconductor industry, including technical approaches and practical challenges. Further, she will give some personal insights on important enabling factors that make a Data Science project successful.

 

Bio: Anja Zernig coordinates Data Science projects at KAI Kompetenzzentrum Automobil- und Industrieelektronik GmbH in Villach, which is a 100% subsidiary of Infineon Technologies Austria AG. Dr. Zernig studied Technical Mathematics at the University of Klagenfurt and received her PhD in 2016. Afterwards, she has been applied as a researcher at KAI, focusing on topics like outlier and anomaly detection, pattern recognition, applied statistical methods and Machine Learning techniques. Since 2019 she is coordinating a team of Data Scientists, involved in various national and international funding projects and acts as a link between the industry and academic collaboration partners. She is supervising researchers and students, dealing with innovative data-analytical concepts within the semiconductor production, testing and optimization and publishes latest scientific insights in different conference and Journal papers. Beside this, Dr. Zernig participates in and supports local Data Science activities, e.g. she is part of the organizing team of the Women in Data Science Villach. In recent times, she is focusing on deployment strategies to guarantee sustainable Machine Learning lifecycles.