Research Assistant / PhD Candidate (all genders) - Research Lab Active AI of the Cluster of Excellence Reasonable Artificial Intelligence

TU Darmstadt stands for excellent and relevant science. We are playing a decisive role in shaping far-reaching processes of global change—from energy transition to artificial intelligence—through outstanding scientific knowledge and innovative academic programmes. We group our cutting-edge research into three fields: Energy and Environment, Information and Intelligence, Matter and Materials. We are a university with strong ties to the Frankfurt Rhine-Main metropolitan region and a very strong international focus. We are committed to European values and European integration.

The Cluster of Excellence 3057 Reasonable Artificial Intelligence, RAI, was selected as one of 70 Clusters of Excellence to receive funding in a highly competitive process. The RAI Cluster of Excellence conducts research focusing on AI systems that acquire human-like communication and thinking skills, as well as the ability to recognize, classify, and adapt independently to new situations. The Cluster of Excellence conducts cutting-edge research at the highest international level with regular publications in flagship venues such as NeurIPS, AAAI, ACL, RSS, CVPR, SIGMOD, ICSE, Nature Communications, Nature Human Behaviour, Nature Machine Intelligence and offers scientists in early career phases the best possible working and research conditions. RAI contributes to Germany's continued expansion of its international competitiveness in artificial intelligence.

The Cluster of Excellence is closely integrated with the Hessian Center for Artificial Intelligence (hessian.AI). The cluster has exclusive access to state-of-the-art GPU power (A100 and H100) through the AI supercomputers fortytwo and fortythree from hessian.AI, providing a reliable basis for cutting-edge research in AI training and inference. The Cluster of Excellence involves researchers from other universities, including the University of Bremen, Goethe University Frankfurt am Main, Saarland University Saarbrücken, the University of Tübingen, and Julius Maximilian University Würzburg.

RAI is structured into four Research Labs. Your tasks will focus on the Active AI Research Lab: A key aspect of intelligence is the ability to quickly adapt and adjust to unexpected changes. Humans and animals can do so continuously throughout their lives by interacting with and exploring their environment, a skill that is essential for their survival. They learn continuously throughout their lives by interacting with and exploring their environment. In contrast, current AI systems do not exhibit the same level of adaptation as training algorithms are unable to extrapolate effectively from observed data. To overcome this limitation, the most common solution is to increase the size of data sets to capture as much of the real-world variance as possible. However, this is not only costly and unsustainable, but also results in systems that are inherently opaque and prone to error. It is also clear that scaling is not the solution this problem which would not only be costly and unsustainable but also will lead to systems that are inherently opaque and prone to failure. To continually function in a meaningful way throughout their life cycle, AI systems need to move beyond the dependence on a large amount of data and instead be proactive, reactive, and adaptive in their interaction with the world. A central question is thus: How can we create AI agents that continuously seek new knowledge for adapting and learning to act in an ever-changing world?

Possible supervisors/mentors with a focus on Active AI

• Prof. Dr. Georgia Chalvatzaki: Interactive Robot Perception & Learning
• Prof. Dr. Carlo D’Eramo: Reinforcement Learning and Computational Decision-Making
• Prof. Dr. Emtiyaz Khan: Adaptive Bayesian Intelligence
• Prof. Dr. Heinz Koeppl: Self Organizing Systems Lab
• Prof. Dr. Martin Mundt: Lifelong Machine Learning
• Prof. Dr. Jan Peters: Intelligent Autonomous Systems Group
• Prof. Dr. Constantin Rothkopf: Psychology of Information Processing

For further information, as well as a list of the participating professors, please refer to the RAI website: https://hessian.ai/projects/reasonable-ai-rai/. See the hessian.AI website under 'Graduate School' for information on what it is like to be a PhD candidate in Germany.

Your tasks will be related to the research conducted in the Research Lab Active AI.

Possible topics for dissertations are:

• Differentiating static and dynamic feature representations from active interactions
• Actively grounding changing representations with symbolic knowledge
• Constructing memories of relevant interactions
• Actively building causal structured world models
• Agent-driven robust and rapid adaptations
• Synergistic meta-learning across parameter- and functional spaces
• Efficient active pruning of models and modules
• Modular uncertainty quantification
• Active reasoning over uncertainties
• Active knowledge and explanations seeking strategies
• Actively seeking unknown data and representations
• Actively seeking reasonable explanations
• Actively seeking modules and system components
• Lifelong learning through synergies
• Lifelong learning and personalization
• Lifelong neurosymbolic learning
• Transactive memory to co-adapt with the surrounding world
• Neurogenesis for dynamic lifelong models
• Neurosymbolic robot learning
• Lifelong reinforcement learning
• Adaptive Deep Learning
• Principles of Information Processing
• Active Deep Learning

Candidates apply for one of the RAI research labs, not for a specific PhD project and not for several labs in parallel. While the doctoral candidates should first discuss their respective research interests and identify possible supervising professors during the first year (lab rotation with permanently assigned mentors), the specific dissertation topics are determined by the beginning of the second year at the latest. The doctoral candidates are then supervised by two RAI professors, preferably across labs.

• University science degree (master's or equivalent) with very good performance in computer science, machine learning and artificial intelligence or related fields
• Very good programming skills, e.g. with deep (probabilistic) learning, compilers and/or robots
• Specific technical knowledge that enables collaboration on the central research questions of the Active AI Research Lab and the cluster
• Very good English skills
• Ability to cooperate in a dynamic and interdisciplinary research environment
• Ability to work both independently and in a team, as well as a high degree of motivation and proactive behaviour

Technical University of Darmstadt offers varied and challenging assignments, freedom to work independently, the latest technologies, good collaboration between colleagues in partnership, needs-based training opportunities and customised personnel development.

Opportunity for further qualification (doctoral dissertation) is given. The fulfillment of the duties likewise enables the scientific qualifications of the candidate.

• Development and organisation – comprehensive in-house training offers, including the opportunity for continuing education and development;
• Annual leave/educational leave – 30 days annual leave (full-time employment) and 5 days educational leave;
• Sustainable and mobile – eligibility to free public transport in the state of Hesse with the LandesTicket Hessen (Hesse StateTicket) in accordance with the currently valid collective agreement, in addition to opportunities to working mobile at times;
• Fit and healthy – free of charge preventive medical check-ups and a wide-ranging subsidised sports programme;
• Work-life balance – flexible working time models, plus BGM (Betriebliches Gesundheitsmanagement – University Health Management);
• Pension scheme – supplementary public service pension scheme (VBL) in accordance with the currently applicable regulations;
• University bicycle
• Family-friendliness/compatibility of family/care/career – (university-run) childcare services, child allowance (based on the collective agreement), childcare programmes during school holidays.

TU Darmstadt intends to increase the number of female employees and encourages female candidates to apply. In case of equal qualifications, applicants with a degree of disability of at least 50 or equal will be given preference. Remuneration is in accordance with the collective agreement for the Technical University of Darmstadt (TV - TU Darmstadt). Part-time employment is generally possible.

By submitting your application, you agree that your data may be stored and processed for the purpose of filling the vacancy. You can find our privacy policy on our webpage.

If you have any questions about this position, please contact Dr. Susann Weißheit, Managing Director RAI, +49 6151 1628548 or susann.weissheit@hessian.ai

Please note the information provided in the application form regarding the application documents to be submitted.