Master Thesis in AI Curricula Development

Author a Landmark Thesis in AI Education. Define the New Standard for Applied AI.

Are you a Master student seeking a thesis project that combines deep academic research with profound, practical impact? Do you believe the key to unlocking AI's potential lies in bridging the chasm between classroom theory and messy, real-world industrial application?

We offer a unique opportunity to conduct your Master thesis at the intersection of AI, education, and industrial automation. Your project will be to design, develop, and validate a comprehensive, state-of-the-art AI curriculum within our Learning Factory. This is not just an academic exercise; you will take ownership of a significant research and development project, creating a robust educational framework that tackles the entire AI lifecycle—from strategic data planning and generation to sophisticated modeling, MLOps, and deployment.

Your central research objective will be to develop and evaluate a curriculum that effectively teaches advanced AI concepts by grounding them in tangible, industrial use cases. You will be the primary driver of this project, from conceptualization to final delivery, culminating in a high-impact Master's thesis and a deployable educational product.

During your assignment you will independently research, define and design complex, multifaceted AI use cases within the learning factory, covering topics such as time series anomaly detection, virtual sensors, explainable AI, predictive maintenance, transformers, reinforcement learning, and GANs in a comprehensive manner, demonstrating clear business relevance.

You will evolve and implement sophisticated strategies for data generation as well as augmentation to address real-world challenges such as data scarcity, noise and imbalance, creating high-quality datasets for learning modules.

Furthermore you will create, train, and implement advanced AI models for your selected use cases and integrate MLOps principles to automate deployment pipelines, model monitoring, and model retraining.

Additionally, you will be responsible for creating a complete, high-quality "Curriculum-in-a-Box" that includes detailed lecture notes, publication-ready documentation, interactive Jupyter notebooks, robust code repositories (via Git), and scalable exercises for teaching at the master's level.

Your job includes developing as well as relocating a methodology for validating the educational effectiveness of the curriculum, for example through pilot workshops, user testing with student groups, as well as qualitative and quantitative analyses of learning outcomes.

Finally you will write a comprehensive master's thesis that documents your research, methodology, results, and contributions in the field of AI education, and meets publication-quality standards.