Bachelor's or Master's Thesis: Use of AI in Maintenance - Job Opportunity at FIR e. V. an der RWTH Aachen

Aachen, Germany
Part-time
Entry-level
Posted: January 17, 2025
On-site
EUR 24,000-28,000 per year (typical German research assistant salary for thesis positions)

Benefits

Flexible work schedule with independent time management
Modern digital workspace environment
Direct exposure to industry-research partnerships
Professional development opportunities
Collaborative team environment
Experience with leading companies and research institutions

Key Responsibilities

Conduct comprehensive literature and market research on AI/ML applications in maintenance
Analyze existing maintenance processes and identify AI optimization opportunities
Develop practical implementation recommendations
Create detailed documentation and actionable insights
Contribute to innovative maintenance strategy development

Requirements

Education

Current enrollment in Bachelor's or Master's degree in Industrial Engineering, Mechanical Engineering, Computer Science or related field

Required Skills

Very good written and spoken English skills Proficiency in MS Office programs Independent and committed work ethic Careful and goal-oriented approach
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Sauge AI Market Intelligence

Industry Trends

The integration of AI in industrial maintenance represents a significant shift from reactive to predictive maintenance paradigms, with the market expected to grow at 25% CAGR through 2025 Manufacturing sectors are increasingly adopting IoT sensors and AI analytics for condition monitoring, creating high demand for specialists who can bridge maintenance and data science The German manufacturing sector is particularly active in Industry 4.0 initiatives, making this research highly relevant to current market needs

Role Significance

Likely part of a 5-10 person research team within the Service Management department
Entry-level research position with significant potential impact on industrial maintenance practices

Key Projects

Development of AI-based predictive maintenance frameworks Process optimization studies for industrial maintenance Implementation strategies for machine learning in maintenance workflows Cost-benefit analysis of AI maintenance solutions

Success Factors

Strong analytical capabilities combined with practical industrial understanding Ability to translate complex AI concepts into actionable maintenance strategies Effective communication skills to bridge technical and operational stakeholders Understanding of both maintenance processes and data science principles

Market Demand

High demand with growing trajectory due to Industry 4.0 initiatives and the critical need for AI integration in traditional maintenance operations

Important Skills

Critical Skills

AI/ML fundamentals with focus on practical applications Understanding of industrial maintenance processes Data analysis and interpretation skills Technical documentation and research capabilities

Beneficial Skills

Programming skills in Python or R Knowledge of industrial IoT systems Understanding of reliability engineering Experience with maintenance management systems

Unique Aspects

Direct involvement in cutting-edge Industry 4.0 research
Combination of academic rigor with practical industrial application
Access to leading industrial partners and research networks
Opportunity to influence future maintenance practices

Career Growth

6-12 months thesis duration with potential for full-time employment in related industrial or research positions

Potential Next Roles

Industrial Data Scientist Maintenance Analytics Specialist Digital Transformation Consultant Industry 4.0 Implementation Manager

Company Overview

FIR e. V. an der RWTH Aachen

FIR e. V. is a renowned research institute at RWTH Aachen University, specializing in industrial management and digital transformation

Leading position in industrial research and innovation, particularly in Industry 4.0 and digital transformation
Centrally located in Germany's industrial heartland with strong connections to major manufacturing companies
Academic research environment with strong industry collaboration, fostering innovation and practical application
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