Deutsches Zentrum für Luft- und Raumfahrt (DLR)
Computer Scientist or Mathematician (f/m/x)
Ulm
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For our Institute for AI Safety and Security in Ulm we are looking for a Computer Scientist or Mathematician (f/m/x), Research assistance in the field of IT and AI security
Das erwartet Sie:
The Institute for AI Safety and Security provides research and development services in the field of AI-related methods, processes, algorithms and execution environments. The focus is on ensuring safety and security for AI-based solutions in ambitious application classes. “Safety and security by design” is a central aspect in this context, since it directly supports future requirements of safety-critical applications that are based on AI or integrate AI-based components. Main Research Areas of the Institute for AI Safety and Security are:
- development processes and methods for safety-critical AI applications
- robust and reliable approaches to safeguard AI methods and algorithms
- safety and security in the context of AI-based applications
- management and use of sensitive data
- execution environments for AI-based applications
- innovative computation methods
The department Safety-Critical Data Infrastructures deals with data and information quality as well as the foundations for building secure, decentralized data infrastructures. The SCD department is also responsible for the secure use, distribution and management of data. The focus here is on the secure provision of data worthy of protection in a highly networked infrastructure. Concepts from the field of distributed systems are primarily used for this. The primary focus here is on technologies in the context of the European GAIA-X initiative (https://www.gaia-x.eu). One of the main tasks is the further development of methods for securing systems related to artificial intelligence. In addition, the research and development of approaches to secure data with regard to quality and attacks in distributed systems is also a priority. Data-driven systems and technologies, such as artificial intelligence, only learn their functionality based on historical data and are no longer explicitly programmed. This inevitably results in the need for a high-quality and highly secure database that is used for training (i.e. learning) the functionality. Another aspect here is the research and analysis of attack scenarios on systems (not only with artificial intelligence) with the help of compromised data, as well as corresponding defence measures. Analysing methods for increasing IT and AI security is therefore an essential and central component of the AI-SCD department's portfolio.
- research and development on methods for determining and improving information security and cyber security of classic IT systems and systems related to artificial intelligence
- research and development on approaches to data regarding attacks on IT systems in general and AI systems
- scientific research on studies and specialised information related to procedures and challenges in the development and implementation of concepts to increase IT security and AI security
- development of security concepts for distributed systems
- embedding the solution approaches (i.e. attacks and mitigation procedures) in distributed systems
- researching and analysing potential attack vectors and deception approaches to IT and AI systems
- development of countermeasures for attacks and deception approaches
- development of an approach for assessing risks and motives regarding attacks on IT/AI systems
- development of methods and approaches in the context of securing classic IT systems (e.g. certificates, authentication, encryption, etc.) and AI systems (attack security, protection concepts, etc.)
- integration into frameworks for AI systems, with the aim of making the researched methodologies directly usable in practice and available to a broad community
- development of protection concepts for IT and AI systems, including risk and requirements analyses for science and industry
- development of methods to relate the impact of security measures to the performance of systems
- implementation of prototypical applications and visualisations with regard to IT and AI security
- analysis of necessary process steps for embedding defence measures in existing process models
- analysis of possible approaches for the integration of technologies for the purpose of maintaining and increasing security in distributed systems
- preparation of scientific (partial) contributions for publications
- derivation of options for action for scientific and industrial applications
- presentation of scientific results
- control and management of externally funded and core-funded projects
- specialist support in the acquisition of national / European third-party funding
Das erwarten wir von Ihnen:
- completed scientific university degree (Master's degree / university diploma) in formal sciences (e.g. computer science or mathematics) or other degree programmes relevant to the job
- strong knowledge of information security
- expertise in the field of artificial intelligence
- strong programming skills (in Python)
- competences in the preparation of complex scientific contexts
- expertise in the field of IT security
- experience in analysing and implementing software solutions
- proficiency in written and spoken English
- general knowledge of German
Unser Angebot:
Das DLR steht für Vielfalt, Wertschätzung und Gleichstellung aller Menschen. Wir fördern eigenverantwortliches Arbeiten und die individuelle Weiterentwicklung unserer Mitarbeitenden im persönlichen und beruflichen Umfeld. Dafür stehen Ihnen unsere zahlreichen Fort- und Weiterbildungsmöglichkeiten zur Verfügung. Chancengerechtigkeit ist uns ein besonderes Anliegen, wir möchten daher insbesondere den Anteil von Frauen in der Wissenschaft und Führung erhöhen. Bewerbungen schwerbehinderter Menschen bevorzugen wir bei fachlicher Eignung.
Weitere Angaben:
- Eintrittsdatum: 01.01.2025
- Dauer: 2 Jahre mit Möglichkeit zur Verlängerung und ggf. Entfristung
- Vergütung: Je nach Qualifikation und Aufgabenübertragung bis Entgeltgruppe E13 TV EntgO Bund.
- Kennziffer: 94578
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