About the Role:

Background and Scientific Context

In the pharmaceutical environment, complete, consistent, and auditable documents (e.g., URS, manufacturer documentation, software change reports) are crucial for quality, compliance, and the correct implementation of requirements.

What You Will Achieve:

Objective of the Master's Thesis

The goal of this master's thesis is the development and systematic evaluation of an AI-supported approach to assist the document review process in Automation Engineering. In particular, it will examine the extent to which selected AI use cases can improve the efficiency and quality of identifying inconsistencies in technical documents compared to manual reviews. Additionally, suitable AI methods (e.g., rule-based approaches vs. NLP/LLM) will be analyzed, and requirements for the design, governance, and use of a compliant AI system will be derived.

Possible Research Questions

• How effective are specific AI use cases (e.g., requirement coverage, consistency checks, or delta analysis) compared to manual reviews in detecting inconsistencies in technical documents?
  How significantly does AI measurably improve the document review process in terms of efficiency and quality?
• What impact does the use of AI have on throughput time and resource expenditure in the document review process within a regulated environment?
• Which AI approaches (e.g., rule-based vs. NLP/LLM) are best suited for the automated review of requirement specifications in terms of completeness and consistency?
• How must an AI-supported system be designed (technology, governance, processes) to efficiently and compliantly support the document review process in Automation Engineering?
• How must an AI-supported system be used, or how must prompting be conducted to achieve repeatable and accurate results, and where are the limits in practical application?
• What are the methodological, technical, and process-related limitations of using AI in the review of technical requirement specifications?
• In which cases does the use of AI reach its limits compared to manual reviews in terms of accuracy, traceability, and reliability in detecting inconsistencies?

Expected Results

• A structured and robust as-is analysis of the current document creation and review process in Automation Engineering.
• Creation of a use case catalog with prioritization and selection of pilot use cases.
• Implementation in the form of a proof-of-concept for the use cases using different technologies.
• Systematic comparison and technological classification of suitable AI approaches.
• Quantitative evaluation of the AI approach and comparison with the existing process in terms of efficiency, quality, and process performance, among others.
• Identification and analysis of the systematic limitations of using AI in the document creation and review process.
• Creation of a guideline for the repeatable application of the AI solution.

Your Qualifications:

• Master's studies in Automation Engineering, Computer Science, Data Science, Process Engineering, Industrial Engineering, or a comparable field.
• Knowledge in the area of AI applications, Natural Language Processing, Information Retrieval, Document Management, or digital quality assurance in text processing/image processing.
• Structured work approach in an environment with high demands on quality, reliability, auditability, and confidentiality.
• Analytical thinking as well as independent and meticulous work style.
• Good German and English skills, both written and spoken.

Desirable:

• Experience with structured document formats (e.g., templates, traceability tables, tables/metadata) and ideally with tools for document review or versioning.
• Enjoyment of interdisciplinary collaboration and applying theoretical concepts in practice.

What We Offer You:

For this important and responsible position, the salary is €2,010.75 gross/month (full-time, collective agreement for the chemical industry).

• Awards as a top employer and certified family-friendly company.
• Comprehensive further education and training opportunities as well as personal development and mentoring programs.
• Diverse career development programs (talent, trainee, apprenticeship programs).
• Employee recommendation and recognition programs, stock purchase plan.
• Active participation in various network groups (e.g., Diversity, Equity & Inclusion; Sustainability).
• A wide range of health offerings (e.g., free vaccinations, psychological counseling, massages).
• Fitness offerings.
• Company events & celebrations.
• Company restaurant with subsidized prices.
• Company childcare / bilingual company kindergarten.
• Good public transportation connections.