Our research lies in the areas of Artificial Intelligence (AI) and Machine Learning (ML). Our goal is to design intelligent algorithms that learn from data continuously following the cumulative nature of human learning, while ensuring that what has been learned is not only correct but also delivers positive social impact in accordance with ethical and legal requirements. Our current focus areas are: continual learning, responsible AI and creative AI. The project will start on Dec. 1st, 2021.
AI and other computer science fields like databases (DB), data structures and algorithms, networking and communication, security, etc., can benefit from each other. For example, in the case of databases, many traditional optimization techniques like query optimization nowadays rely on AI; on the other hand, DB techniques like indexing can optimize AI models. Likewise, AI is used nowadays to optimize data structures, but knowledge of data structures and algorithms is also required for AI/ML.
This position aims at research and development on improving the teaching of AI/ML subjects in computer science. Tasks include studying how AI is revolutionizing other CS fields but also how AI relies upon foundations from these fields; integration into other computer science subjects like algorithms and data structures, databases, security, etc., selecting appropriate examples and use cases from these fields, etc.
Within the framework of the externally funded research project, the opportunity for writing a doctoral-thesis is granted.
Applicants should hold an MSc or Diploma in Computer Science with a focus on Artificial Intelligence/ Machine Learning/ Data Science.
- Sound understanding of Machine Learning and Artificial Intelligence;
- very good knowledge of AI frameworks (Tensorflow, pytorch, Keras, …);
- excellent programming skills (Python, Java, …);
- good knowledge of core computer science skills (algorithms and data structures, programming, databases, …);
- teaching experience (e.g., as teaching assistant) and warm interest in teaching and didactics of AI;
- understanding and warm interest in AI responsibility aspects (bias and fairness, explainability, …);
- excellent written and verbal communication skills;
- critical thinking and independent work;
- willingness to learn, appreciation for team work.
Applications should be sent by e-mail, together with significant documents, indicating the reference code, in PDF format (preferably as one document) to Prof. Dr. Eirini Ntoutsi: firstname.lastname@example.org or postal to:
Freie Universität Berlin
Fachbereich Mathematik und Informatik
Institut für Informatik
AG Künstliche Intelligenz und Maschinelles Lernen
Mrs. Prof. Dr. Eirini Ntoutsi
14195 Berlin (Dahlem)
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