Research Assistant / PhD Candidate (all genders) - Research Lab Observational 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 Observational AI Research Lab: The goal of Observational AI (OAI) Lab is to establish the algorithmic foundations for AI models that (1) seamlessly combine observational information from different modalities, handling missing modalities; (2) exhibit competence at low-level perception, high-level reasoning, and commonsense knowledge; (3) permit themselves to be combined in a modular manner – the building blocks will be malleable and respond flexibly to new situations and tasks, while skillfully handling familiar ones; (4) offer themselves to be explained in a symbolic manner, understandable to humans and other AIs alike. Thus, OAI is contributing to enabling AIs that have more reasonable qualities and are better suited for real-world deployment in observational tasks.

Possible supervisors/mentors with a focus on Observational AI

• Prof. Dr. Iryna Gurevych: Natural Language Processing
• Prof. Dr. Anna Rohrbach: Multimodal Grounded Learning
• Prof. Dr. Marcus Rohrbach: Multimodal Reliable Artificial Intelligence
• Prof. Dr. Stefan Roth: Visual Inference
• Prof. Dr. Simone Schaub-Meyer: Image and Video Analysis
• Prof. Dr. Justus Thies: 3-D Graphics and Vision
• Prof. Dr. Isabell Valera: Machine Learning

For further information, as well as a complete list of the participating professors, please refer to the RAI website: e: 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 Observational AI Research Lab.

Possible topics for dissertations are:

• Combining different modalities in a modular fashion
• Fusion and communication of modalities
• Adding new modalities
• Balancing modality contributions
• Dynamic modality sampling
• Perceiving, reasoning, and knowing
• Perception in low-shot scenarios
• Relational perception
• Reasoning: the neuro-symbolic way
• Knowledge integration
• Modularity in tasks
• Decomposing tasks, composing results
• Perspective optimization of module composition
• Pivotal module composition
• Efficiently personalizing module composition
• Reasonable observational AI with explanations
• Composable explanations
• Composition and reasoning via explanations
• Counterfactual explanations for task decomposition
• Explanations with model-human interactions

• 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, and/or experience in modalities such as NLP or computer vision
• Specific technical knowledge, that enables collaboration on the central research questions of the Observational AI research lab and the cluster 
• Deep Learning Frameworks (e.g., Pytorch, Tensorflow) 
• Training Deep Learning Models
• Very good English skills (written and spoken)
• 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.