Faculty of Computer Science
The Faculty of Computer Science is a young and dynamic research-oriented faculty with several internationally visible research groups in key areas of Computer Science, including Algorithms, Data Science, AI, Systems (in particular, Security and Software Engineering), and Human-Centered Computing.
The faculty operates and accesses specialised laboratories and computing infrastructures that support empirical and applied research, including facilities for data-intensive computing, security and privacy research, robotics, and human–computer interaction. It also has an excellent track record in theoretical computer science. It offers a broad portfolio of degree programmes at bachelor’s, master’s, and doctoral levels. More than 2500 students are enrolled across these programs, supported by the Studies Service Center of Computer Science.
Doctoral education is focused in the UniVie Doctoral School Computer Science, DoCS, and supported by externally funded programs. Candidates work on core topics in Computer Science and contribute to
collaborative research projects within the University of Vienna and with national and international partners.
Departments/Research Focus
Benjamin Roth
Research Focus
Our research focuses on the explainability, interpretability, and personalization of Large Language Models (LLMs). We develop methods to analyze how LLMs represent, reason, and interact, linking technical innovation with human-centered evaluation. Current projects address (1) standardized benchmarks for LLM trustworthiness and compliance with EU AI Act and GDPR, (2) explainable and controllable model behavior, including persona-based prompting and linguistic convergence, and (3) transparent evaluation methodologies for understanding generalization, calibration, and reasoning abilities. Our group combines computational, linguistic, and ethical perspectives, contributing to responsible AI research and fostering interdisciplinary collaboration across computer science, digital humanities, and philosophy.
Research environment
The postdoc will join the Natural Language Processing Working Group (2 professors, 2 postdocs, 8 PhD students), embedded in the Research Group Data Mining and Machine Learning (7 professors, 27 researchers). Members are active in the ACL community (local co-chairs of ACL 2025, KONVENS organizers, ARR/TACL editors). The group provides access to a high-performance Slurm cluster with multiple servers equipped with NVIDIA H100/H200 GPUs and over 2 TB RAM per node. Excellent grant-writing support is available within the group and through the University Research Service Office. The environment fosters interdisciplinary collaboration across Computer Science, Philological and Cultural Studies, and partner institutions (e.g. ÖAW, WWTF). Successful candidates have access to funding for conference travel in accordance with faculty regulations.
Expectations towards postdoctoral fellows in this programme
Postdoctoral fellows are expected to develop and sharpen an independent research profile that complements the NLP group’s focus on explainability, interpretability, and responsible AI. They should aim for high-impact publications in leading NLP and AI venues (e.g. ACL, EMNLP, AAAI) and actively collaborate with group members and interdisciplinary partners. Fellows are encouraged to pursue competitive research grants (e.g. MSCA, FWF, WWTF, ERC StG) to strengthen their academic independence and career prospects. They will benefit from mentoring and integration into an active research environment, with a strong publication culture, international collaborations, and opportunities to engage in the University’s growing AI and Digital Humanities initiatives.
Possible research themes or topics for postdoctoral projects
- Explainability of AI systems: technical and human-centered perspectives (discourse, pragmatics, usage context).
- Explanations for complex AI agents: multi-faceted explanations for multi-agent and decision-support environments.
- Measurement of LLM properties: standardized evaluation aligned with EU AI Act and GDPR.
- Small LLMs and agent systems for academia: controllable, open-source systems enabling transparent and more sustainable research.
Weblink for further information:
https://dm.cs.univie.ac.at/index.php?id=1910
Email: benjamin.roth(at)univie.ac.at
Edgar Weippl
Research Focus
applied it security; software security; AI security;
Research environment
applied research; close collaboration with companies; SEC leads a COMET research center (SBA Research); tight coooperation with other Austrian universities in the area of information security, such as TU Wien, TU Graz.
Expectations towards postdoctoral fellows in this programme
great publications and interest in collaboration with existing security groups, our CD labs, etc.
Possible research themes or topics for postdoctoral projects
open to all aspects of applied information security
Weblink for further information:
http://sec.cs.univie.ac.at
Email: edgar.weippl(at)univie.ac.at
Atakan Aral
Research Focus
My research focuses on resource management and intelligent services across the edge-cloud continuum, with a particular emphasis on edge AI, sensor networks, and sustainable computing. We design algorithms and systems that jointly optimize performance, energy consumption, and reliability in distributed infrastructures, ranging from low-power IoT devices to data centers. Current projects include AI-driven environmental monitoring in remote areas with scarce power and connectivity, secure and resilient monitoring of critical energy and water infrastructures, and neuromorphic and federated learning methods that bring adaptive intelligence close to where data is generated and used for decision-making. Building on my experience and strong preference for interdisciplinary research, postdoctoral fellows can connect these topics to a wide range of application domains, including climate resilience, smart cities, digital health, precision agriculture, mobility, Industry 4.0, and robotics.
Research environment
We offer a dynamic, international, English-speaking environment with close ties to systems, AI, sustainability, and data-driven modeling. Our group operates several edge and IoT testbeds, GPU servers, and access to the Austrian Scientific Computing (ASC) for large-scale experiments. We are partners in international projects, such as CHIST-ERA SWAIN and TROCI, and participate in university-wide initiatives on digitalization and environmental research. Postdoctoral fellows will have access to office space, high-end hardware, and technical support, as well as opportunities to work with excellent PhD and MSc students, and benefit from a strong seminar culture. They receive mentoring for fellowship and grant applications, as well as encouragement to build their own collaborations with other faculties and external partners. Successful candidates also have access to funding for conference travel in accordance with faculty regulations.
Expectations towards postdoctoral fellows in this programme
I expect postdoctoral fellows to develop an independent research profile while actively contributing to the group’s collaborative projects. Fellows should be motivated to design, implement, and publish high-quality research, co-supervise MSc and PhD students, and help maintain and extend our experimental infrastructure and open-source software. I value openness, reliability, and a constructive, inclusive working style, as well as clear communication in English. Fellows are encouraged to take leading roles in international collaborations and community service, co-write grant proposals (e.g., FWF, EU, MSCA, ERC), and engage in teaching or mentoring activities that strengthen their CV and prepare them for the next career step, whether that is a tenure-track position or an advanced industry role.
Possible research themes or topics for postdoctoral projects
Possible postdoctoral projects include: (i) sustainable edge AI and neuromorphic sensing for environmental or infrastructure monitoring (e.g. pollution, natural disasters, biodiversity); (ii) trustworthy, privacy-preserving learning over distributed IoT data, including federated and personalised learning; (iii) energy-aware scheduling, fault tolerance, and resilience mechanisms for the edge-cloud continuum and scientific workflows; (iv) digital twins of cyber-physical systems that integrate data-driven models with domain knowledge and uncertainty quantification; and (v) frameworks and benchmarks that make edge AI systems more reproducible, explainable, and accessible to other scientific domains. Please note that this list is not exhaustive, and I explicitly welcome postdoctoral fellows to propose their own topics within the group’s broader interests in intelligent distributed systems.
Weblink for further information:
https://cs.univie.ac.at/atakan.aral
Email: atakan.aral(at)univie.ac.at
Karen Azari
Research Focus
My area of research is cryptography and I specialize in formal security definitions and mathematical security proofs for cryptographic protocols. In particular, I work on group messaging, proof systems for decentralized systems, and (foundations of) resource-restricted cryptography.
Research environment
My research group is embedded in the "Theory and Applications of Algorithms" group and by October 2026 will comprise three PhD students under my supervision. There are several other research groups in and around Vienna working on cryptography, with whom we collaborate closely. We have regular joint research meetings, currently taking place every other week at TU Vienna, where we discuss recent results.
Expectations towards postdoctoral fellows in this programme
A postdoc in our group must have strong interest in theoretical aspects of cryptography and be open for collaboration. They should strengthen and broaden our group's research profile. While postdoc researchers are expected to show a decent level of independence, I am happy to give advice wherever needed and will do my best to support them on their career path.
Weblink for further information:
https://homepage.univie.ac.at/karen.azari/
Email: karen.azari(at)univie.ac.at
Wilfried Gansterer
Research Focus
My research interests are in the areas of efficient and reliable numerical algorithms and high performance computing; in particular in the interaction between algorithms, their implementation and properties of the environment where they are executed, and in quantitatively understanding influence factors on sustained performance in realistic settings. This includes in mixed precision algorithms as well as efficient parallel and distributed numerical algorithms which can tolerate faults in unreliable environments.
These aspects are also highly relevant in modern algorithms for machine learning and AI, e.g., studying how to increase efficiency in neural network training and inference without compromising the quality of the results.
Moreover, I am investigating efficient and scalable approaches at the algorithmic level for achieving robustness and resilience against random perturbations (silent data corruption or node failures) as well as against targeted adversarial attacks.
Research environment
You will be integrated into the Research Group Theory and Applications of Algorithms of the Faculty of Computer Science at the University of Vienna, which comprises researchers with expertise in numerical computing, combinatorial algorithms, algorithm engineering and cryptography. You will benefit from a very welcoming environment with many young researchers that is very stimulating for research and open for collaboration.
You will have access to travel funds in accordance with faculty regulations.
Expectations towards postdoctoral fellows in this programme
strong motivation and clear dedication to perform high quality research, interest in pursuing an academic career, a high degree of independence in research activities combined with the willingness to cooperate, good communication skills, willingness to participate in supervising and mentoring students at all levels
Possible research themes or topics for postdoctoral projects
open for all topics which connect well to my research interests
Weblink for further information:
https://taa.cs.univie.ac.at/
Email: wilfried.gansterer(at)univie.ac.at
Gramoz Goranci
Research Focus
I am broadly interested in algorithm design and its connections to optimization, graph theory, and machine learning. Much of my research has centered around the design of fast dynamic algorithms for classic and novel large-scale optimization problems with both theoretical guarantees and practical efficiency. My work brings together tools from many areas, such as combinatorial data structures, algorithmic graph theory, numerical linear algebra, and metric embeddings.
Research environment
Our subgroup *Fast and Dynamic Algorithms* currently consists of three PhD students and one postdoctoral researcher and is part of the research group *Theory and Applications of Algorithms (TAA)*. We have a strong track record of publishing at flagship venues in theoretical computer science, including STOC, FOCS, and SODA. In recent years, our work has also appeared at ICML and NeurIPS, two of the leading conferences in machine learning.
We offer a diverse and vibrant research environment in which collaboration is strongly encouraged, and mutual scientific growth is central to our team culture. The successful candidate will benefit from a broad research network, both within Austria and internationally. Additionally, the host will support the candidate in navigating the academic job market and provide guidance on applications for independent research funding. The successful candidate will also have access to funding for conference travel in accordance with faculty regulations.
Expectations towards postdoctoral fellows in this programme
As a postdoctoral researcher joining our group, we expect a motivated individual with a strong record in theoretical algorithm design and an openness to exploring new research directions. Our group primarily focuses on developing fast algorithms and data structures for graph-based optimization problems; prior experience in this area is desirable but not strictly required. We expect that you are eager to establish an independent research profile while simultaneously collaborating on joint projects with other group members. Strong time-management skills and the ability to balance multiple aspects of the position are very important criteria.
Weblink for further information:
https://taa.cs.univie.ac.at/
Email: gramoz.goranci(at)univie.ac.at
Torsten Möller
Research Focus
Our research group focuses on various aspects of visual data analysis. On the one hand, we seek to broaden the scope of visual literacy research, expanding its scope from performance-based metrics to more human-centered concepts inspired by learning sciences. On the other hand, we employ human-centered design approaches to enhance the understanding of multidimensional spaces (4-7D). Additionally, we explore physical data representations, utilizing advanced fabrication methods to create artifacts that support users in the exploration of multi-variant and multidimensional spatial data.
Research environment
We strive to create and maintain a collaborative environment both within the group and with external peers. Our group frequently interacts with researchers from communication science, STS, and psychology. Our group provides researchers with access to state-of-the-art computational infrastructure, ranging from GPU clusters to 3D printers. Successful candidates have access to funding for conference travel in accordance with faculty regulations.
Expectations towards postdoctoral fellows in this programme
Postdocs in our group are encouraged to build a resume at this important early stage of a research career. We integrate the aspects of teaching and research in our day-to-day operations for all members. Frequent publications in highly reputable venues, as well as securing funding through grant applications, are crucial for this. While teaching responsibilities vary depending on the contract, supervising students during bachelor's and master's theses, as well as advanced research projects, and mentoring and supporting PhD students are essential functions of a postdoctoral fellow.
Weblink for further information:
https://vda.cs.univie.ac.at
Email: torsten.moeller(at)univie.ac.at
Please see Faculty of Chemistry.
Dominik Kopczynski is PI of a computer science-oriented working group at the Faculty of Chemistry. You'll find him at the department of Analytical Chemistry.