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Research Assistant in Mathematical Image Computing - Job Opportunity at Universität zu Lübeck

Lübeck, Germany
Full-time
Entry-level
Posted: March 8, 2025
Hybrid
EUR 55,000 - 65,000 annually based on TV-L E13 scale for academic research positions in Germany

Benefits

Comprehensive pension plan with high employer contribution
Flexible work arrangements including remote options
Annual performance bonus
Subsidized public transport ticket
Extensive professional development programs
30 days annual vacation plus additional holidays
Subsidized campus dining
Access to university sports facilities
Comprehensive health management program

Key Responsibilities

Lead research projects in mathematical image processing and algorithm development
Develop and analyze novel mathematical models with focus on medical applications
Publish findings in high-impact international journals and present at conferences
Support teaching activities in Mathematics, Medical Engineering and Computer Science programs
Contribute to collaborative projects with Fraunhofer MEVIS

Requirements

Education

Master's or Diploma degree in Mathematics, Computer Science or closely related field

Experience

Strong academic background required, no specific years of experience stated

Required Skills

Advanced applied mathematics Machine learning or quantum computing expertise Image processing knowledge Proficiency in modern programming languages (Python, C++) GPU/CPU implementation experience Excellent German and English communication skills
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Sauge AI Market Intelligence

Industry Trends

Growing integration of AI and quantum computing in medical imaging analysis Increased demand for specialized mathematical expertise in healthcare technology Rising importance of GPU-accelerated computing in medical research Expansion of collaborative research initiatives between academic and industrial partners

Role Significance

Typical research group structure of 5-8 researchers including PhD students and postdocs
Entry-level research position with significant autonomous research responsibilities and potential for academic career development

Key Projects

Development of novel mathematical models for medical image analysis Implementation of quantum computing algorithms for healthcare applications Collaborative research projects with medical technology industry partners

Success Factors

Strong foundation in theoretical mathematics combined with practical programming skills Ability to bridge theoretical concepts with practical medical applications Excellent communication skills for academic publishing and teaching Self-motivated research approach with focus on innovation

Market Demand

High demand for specialists in mathematical imaging and computational medicine, particularly with quantum computing knowledge

Important Skills

Critical Skills

Advanced mathematical modeling skills essential for developing novel medical imaging solutions Programming expertise crucial for implementing theoretical concepts Research methodology and academic writing capabilities for successful PhD completion

Beneficial Skills

Knowledge of medical imaging systems and healthcare technology Experience with quantum computing frameworks Project management and teaching abilities

Unique Aspects

Rare combination of mathematical research with direct medical applications
Close collaboration with Fraunhofer Institute offers unique industry exposure
Strong focus on emerging technologies like quantum computing in medical context

Career Growth

3-year PhD position with potential for academic or industry career progression

Potential Next Roles

Postdoctoral Researcher Research Group Leader Professor Industry Research Scientist

Company Overview

Universität zu Lübeck

Leading German public university specializing in life sciences and medical technology

Strong reputation in medical research and computational science with excellent industry connections
Major academic institution in northern Germany with international research networks
Collaborative academic environment with strong focus on interdisciplinary research and innovation
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