Doctoral Researcher in the field of Neurosymbolic AI for Scientific Workflows

The position is situated in the context of a research project on the development, evaluation, and integration of Neurosymbolic AI systems to support scientific workflows. The objective is to develop a data-driven, adaptive, Human-in-the-Loop, and semi-autonomous pipeline that makes research processes more efficient, transparent, and reproducible.

In connection with this position, you can expect in particular the following tasks:

Design, development, and implementation of Neurosymbolic AI and integrated LLM architectures
Integration of Large Language Models (LLMs) and agentic systems into scientific work processes
Design and evaluation of multi-agent architectures to enhance research workflows
Development of data-driven models and analysis of heterogeneous data sources for decision support
Conceptualization and execution of experiments for systematic evaluation and scientific methodology
Publication of research results in international journals and at top-tier scientific conferences

Who are we looking for?

A prerequisite for employment is a completed academic university degree (Master’s or equivalent) in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field.

Additionally advantageous are:

Very good knowledge of Machine Learning and/or Deep Learning
Solid programming skills (e.g., Python)
Experience in working with Large Language Models and/or agent systems
Very good English language skills, both written and spoken