Master Thesis: Advancing Ion Beam Tuning Prediction in Semiconductor Manufacturing

Explore the cutting-edge realm of semiconductor manufacturing! Your thesis will revolve around ion implantation equipment. Your mission: develop an AI model that goes beyond predicting just the subsequent tuning outcome, foreseeing multiple upcoming tunings.

Your Challenge

In semiconductor manufacturing, ion beam tuning is critical for each process specification change at implantation.1 The key to success lies in avoiding costly timeouts caused by unsuccessful tuning. As part of your thesis, you’ll work on an AI prediction model that estimates the tuning outcome for the consecutive implantation process as the first step. Building on this model, the final goal is to extend it to predict outcomes for multiple upcoming tunings.

Deep Learning in Focus

Over the course of an 8–12-month internship, you’ll dive into the realm of deep learning models. Within a team of master and PhD students, you will be developing cutting-edge techniques that empower predictive maintenance, revolutionizing semiconductor processes.

Your Profile

As a passionate computing and data enthusiast, you’re the perfect candidate for this exciting challenge. Your solid experience with Python, including scikit-learn and TensorFlow/Keras/Pytorch, makes you wellprepared for the task. Fluency in written and spoken English is essential, with German language skills as a plus. While not mandatory, familiarity with SQL will be advantageous. The ability to query data from databases will enhance your exploration of predictive insights.

Join the Frontier of Ion Beam Tuning Prediction!

Embrace the opportunity to be at the forefront of semiconductor advancements. Your contributions to developing an AI model that predicts multiple upcoming tunings will shape the future of manufacturing.

Our company offers a flexible work environment, allowing remote work from home. Employees can also dedicate office hours to academic pursuits, including thesis writing. Join us to thrive personally and professionally.

This position is subject to the collective agreement for workers and employees in the electrical and electronics industry (full-time), employment group D (basic level) for master students:


Preferred start date: October 2023

Please attach the following documents (German or English) to your application and send it to andreas [dot] laber [at] infineon [dot] com:

  • CV
  • Letter of motivation
  • Certificate of matriculation in a master program at a university
  • Latest transcript of records (not older than six months)


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:



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.



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

The University of Klagenfurt also offers:

  • Personal and professional advanced training courses, management and career coaching
  • Numerous attractive additional benefits, see also
  • 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

  • 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

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 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



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.