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Research Assistant / HiWi / Master Thesis Machine Learning in Microfluidics Applications (f/m/d) - Job Opportunity at Hahn-Schickard-Gesellschaft für angewandte Forschung e.V.

Freiburg, Germany
Full-time
Entry-level
Posted: May 23, 2025
On-site
€35,000-45,000 annually for research assistant positions, with potential for thesis students to receive €800-1,200 monthly stipends, reflecting the specialized nature of AI-microfluidics intersection and Baden-Württemberg's competitive research sector compensation

Benefits

Team events and company social activities that foster collaboration and networking within the interdisciplinary research environment
Flexible working hours and duration arrangements that accommodate academic schedules and research project demands
Access to state-of-the-art laboratory facilities and cutting-edge microsystems technology equipment
Professional development through expert guidance and mentorship in specialized research areas
Comprehensive health and wellness programs including Hansefit membership for maintaining work-life balance
Meal allowances for campus canteen and surrounding dining options
Monthly public transportation subsidies supporting sustainable commuting

Key Responsibilities

Lead critical machine learning initiatives in microfluidics applications, driving innovation from microtumor detection to precision dispensing system optimization that directly impacts point-of-care diagnostic advancement
Execute comprehensive image annotation protocols for extensive microscopic datasets, establishing the foundational data infrastructure essential for AI system development and validation
Collaborate strategically within interdisciplinary research teams to advance scientific understanding in microfluidics and laboratory automation, contributing to breakthrough discoveries
Develop and optimize AI training and validation systems that enhance automated arrangement of viable microtumors in multiwell plates and improve volume estimation accuracy for dispensing jets
Partner closely with senior researchers to push technological boundaries and establish new methodologies in the intersection of machine learning and microsystems technology

Requirements

Education

Bachelor's degree in Computer Science/ Engineering or a related field

Experience

Experience in image annotation or a similar role, particularly with microscopic images

Required Skills

Familiarity with machine learning processes and a keen interest in AI applications in the scientific field Excellent collaboration skills, with a proactive approach to interdisciplinary teamwork Creative thinking and problem-solving abilities Proficiency in the Python programming language First experiences in machine learning Proficient in either English or German
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Sauge AI Market Intelligence

Industry Trends

The convergence of artificial intelligence and microfluidics represents one of the fastest-growing segments in biotechnology, with the global microfluidics market projected to reach $35 billion by 2027, driven primarily by point-of-care diagnostic applications and personalized medicine initiatives. Machine learning applications in laboratory automation are experiencing unprecedented demand as research institutions and biotech companies seek to accelerate drug discovery processes and improve diagnostic accuracy through automated image analysis and pattern recognition. The integration of AI-powered systems in medical device development is becoming mandatory rather than optional, with regulatory bodies increasingly requiring robust validation datasets and automated quality control systems for approval of diagnostic devices.

Role Significance

Likely part of a 5-8 member interdisciplinary research team within the Laboratory Automation group, collaborating with biologists, engineers, and data scientists in a matrix organizational structure typical of research institutions
Entry-level position with significant growth potential, offering direct exposure to cutting-edge research methodologies and serving as a gateway to specialized career paths in AI-enabled medical technology development

Key Projects

Development of automated tumor detection systems for cancer research applications Creation of machine learning algorithms for precision fluid handling in diagnostic devices Validation and optimization of AI models for real-time quality control in laboratory automation systems

Success Factors

Ability to bridge technical machine learning concepts with biological applications, requiring both computational expertise and scientific curiosity about medical applications Strong collaborative skills essential for working effectively in interdisciplinary teams where communication between technical and scientific domains is critical Attention to detail in image annotation and data preparation, as the quality of training datasets directly impacts the performance of AI systems in medical applications Adaptability to rapidly evolving technological requirements and research priorities in the fast-paced field of AI-enabled medical device development

Market Demand

Very high demand driven by the critical shortage of professionals with combined expertise in machine learning and microfluidics, particularly in the German research landscape where government funding for AI-enabled medical technology research has increased by 40% in recent years

Important Skills

Critical Skills

Python programming proficiency is essential as it serves as the primary language for machine learning model development, data processing, and integration with laboratory automation systems in the research environment Image annotation experience is crucial because the quality and accuracy of annotated training datasets directly determine the performance of AI systems in medical applications, where precision can impact diagnostic outcomes Machine learning fundamentals are vital for understanding algorithm selection, model optimization, and validation processes that ensure AI systems meet the stringent requirements of medical device applications

Beneficial Skills

Knowledge of computer vision techniques would accelerate contribution to microscopic image analysis projects and enhance ability to optimize detection algorithms for biological applications Understanding of microfluidics principles would facilitate communication with interdisciplinary team members and enable more effective contribution to system design and optimization discussions Experience with scientific writing and documentation would support thesis development and contribute to research publication efforts that enhance both personal career prospects and institutional research impact

Unique Aspects

Rare opportunity to work at the intersection of artificial intelligence and microfluidics, a highly specialized field with limited global expertise and significant commercial potential
Direct involvement in developing AI systems for medical applications, providing exposure to regulatory requirements and validation processes essential for commercial medical device development
Access to extensive microscopic imaging datasets and state-of-the-art laboratory facilities that few academic or commercial organizations can provide
Potential for thesis work that could contribute to patent applications and commercial product development, offering both academic credentials and industry experience

Career Growth

Typical progression to mid-level positions within 2-3 years, with potential for advanced research roles or industry leadership positions within 5-7 years given the specialized expertise in AI-microfluidics applications

Potential Next Roles

Machine Learning Engineer in medical technology companies Research Scientist positions in pharmaceutical or biotech organizations PhD researcher in computational biology or biomedical engineering Product Development Engineer for diagnostic device manufacturers

Company Overview

Hahn-Schickard-Gesellschaft für angewandte Forschung e.V.

Hahn-Schickard is a prominent applied research organization in Germany's Baden-Württemberg region, specializing in microsystems technology with over 300 employees across four locations, representing one of Europe's leading institutes for translating academic research into commercial applications

Recognized as a key player in the German innovation ecosystem, particularly strong in the transition from research to industrial application, with established partnerships with major automotive, medical technology, and industrial automation companies
Strategically positioned in Baden-Württemberg, one of Europe's most innovative regions, with the Freiburg location benefiting from close proximity to Albert-Ludwigs-Universität Freiburg and access to the region's extensive biotech and medical technology cluster
Academic-industry hybrid environment that combines rigorous scientific methodology with practical application focus, offering researchers the opportunity to see their work translated into real-world solutions while maintaining intellectual freedom typical of research institutions
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