Research Assistant (Postdoc / Postdoctoral Researcher) AGI Research & Cognitive AI – AGI beyond LLMs (Focus: ARC-AGI-3) (m/f/d)

While most of the current AI research focuses on large generative models, our research group pursues the goal of exploring approaches to Artificial General Intelligence (AGI) that go beyond LLM-centred paradigms. A postdoctoral candidate or a postdoctoral candidate with interest in the development of new research approaches and directions, for example in the field of phenomenology of cognition (e.g. formalisation of concepts such as final followers, agency, meaning or experience in verifiable computer-assisted models, acquisition of skills, affordances). Knowledge in the field of machine learning and artificial intelligence as well as a pronounced mathematical background are expected. The workplace requires a strong professional interest in the exploration of several research directions on the way to general artificial intelligence, including current generic AI approaches and alternative paradigms beyond LLM-centric models. ARC-AGI-3 is a key reference framework for defining and evaluating the progress of research. The aim of the research is to further develop skills within the meaning of the ARC-AGI-3 approach, in particular with regard to robust generalization, abstraction and problem solving beyond pure pattern recognition. Your activity includes Cooperation with ARC-AGI-3 oriented research in close cooperation with team members, including the development of implementations and systematic evaluation of methods. Participation in the development of research approaches beyond LLM-centric methods and implementation of hypotheses in concrete models, experiments and measurable project results within the project framework. Conception and implementation of reproducible experimental pipelines (including baselines, ablation studies and robustness and out-of-distribution tests), including the use of game-based or game-like environments, if appropriate. Planning and structuring of research activities, including the definition of milestones, regular progress reporting and iterative adaptation based on empirical results and expert feedback. Development, documentation and maintenance of reproducible research codes, including versioning, automation of training and evaluation courses, and use of AI-based development tools. Preparation and communication of research results (e.g. documentation, internal presentations), participation in scientific publications and preparation of open research artifacts (e.g. code and experiment configurations).

Complete academic studies (master or equivalent) in a relevant course of study such as artificial intelligence, machine learning, computer science, mathematics, physics or a closely related subject area. Completed doctorate (PhD) in one of the mentioned or a professionally closely related fields. Knowledge of machine learning and artificial intelligence, including interest in alternative approaches beyond standardized deep learning methods. detectable experience in scientific research (e.g. through publications, conference contributions or comparable scientific achievements). Very good programming knowledge in Python as well as experience in the development and documentation of reproducible research codes (e.g. with PyTorch or comparable frameworks). Practical experience in using AI-based development and coding tools (e.g. code assistants) to support development, experimentation and research processes. Finded mathematical knowledge with relevance for AI/ML (e.g. dynamic systems, optimization, representation learning or related areas; including but not limited to algebraic topology). proven experience in at least one of the following interdisciplinary research areas: Artificial Intelligence and Psychology / Cognition (e.g. cognition-inspired modeling, human learning and thinking), or related interdisciplinary research approaches related to AI.

Very good knowledge of English in word and writing. Required qualifications Certified scientific contributions (e.g. publications, preprints submitted for assessment or substantial open-source contributions) in the field of natural, bio- or cognition-inspired AI (e.g. neuro-inspired learning processes, cognitive architectures, biologically plausible learning methods or self-organisation). Experience with evaluations in interactive environments (e.g. games), reinforcement learning, planning, world models, causal modeling or methods for robust generalization. Embossed written expressiveness and experience in interdisciplinary cooperation, including participation in scientific publications.

Our aim is to rethink and innovate the provision and use of research data and information. In the TIB research and development department, you have the opportunity to advance your scientific further qualification and research career in a dynamic and excellent research environment. We offer an intellectually inspiring environment with entrepreneurial thinking, embedded in a leading technical university and one of the largest information centres in the Leibniz community. With the L3S research centre at Leibniz Universität Hannover, one of the world's leading research institutes in the field of Web & Data Science, there is a close cooperation within the framework of the Leibniz Joint Lab Data Science & Open Knowledge. Last but not least, we value an open and creative working environment where it is fun to work. In addition, we offer A community-oriented workplace in the public service on the basis of the TV-L with a remuneration according to the remuneration group 13 TV-L. A special payment at the end of the year as well as 30 days holiday a year at a five-day week as well as additional free days on Christmas Eve (24.12.) and New Year's Eve (31.12.). A flexible workplace in time and space with offers for the reconciliation of work and family, such as mobile work and flexible working time models. A modern workplace in a central location of Hanover with a collegial, attractive and versatile work environment. An employer with a wide range of continuing and continuing training, occupational health promotion and pension provision for the public service (VBL). Employee discount in the students of the Studentenwerk Hannover as well as the possibility to use the versatile offers of the University Sports Hannover. Individually responsible and forward-looking activities that offer variety and leave room for personal development. .