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PhD Position - Deep Learning for Biomedical Image Analysis - Job Opportunity at Universitätsklinikum Hamburg-Eppendorf (UKE)

Hamburg, Germany
Part-time
Entry-level
Posted: February 10, 2025
On-site
EUR 47,000-55,000 annually (based on TVöD/VKA E13, 80% position)

Benefits

Comprehensive healthcare coverage through UKE's medical center network
Subsidized Deutschlandticket for sustainable commuting
Bicycle leasing program with maintenance support
Extensive professional development through UKE Academy
Work-life balance support including childcare assistance
On-site wellness and sports programs
Multiple dining options with health-focused choices
Family-friendly policies including vacation childcare

Key Responsibilities

Design and implement novel deep learning algorithms for medical image analysis
Develop state-of-the-art computer vision solutions using CNNs, Vision Transformers, and Foundation Models
Lead research in supervised and unsupervised learning approaches for microscopy data analysis
Collaborate with clinical researchers to predict disease progression patterns
Contribute to interdisciplinary research projects within bAIome initiative

Requirements

Education

Master's degree in computer science, mathematics or related fields

Required Skills

Deep learning frameworks (PyTorch, TensorFlow, Keras) Python programming Linux environments scikit-learn scikit-image OpenCV Good communication skills English language fluency

Certifications

Proof of measles immunity
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Sauge AI Market Intelligence

Industry Trends

Biomedical AI is experiencing rapid growth with increased funding and research opportunities, particularly in European medical institutions Integration of foundation models in healthcare is creating new research directions and opportunities for novel methodologies Growing emphasis on explainable AI in medical applications is driving method development Increased collaboration between clinical and AI research teams is becoming standard in leading medical centers

Role Significance

Small to medium research group (typically 5-10 members) within larger institutional framework
Entry-level research position with significant potential for academic growth and publication impact

Key Projects

Development of novel deep learning architectures for microscopy image analysis Clinical validation studies for AI-based diagnostic tools Integration of explainable AI methods in medical imaging workflows Collaborative research projects with clinical departments

Success Factors

Strong foundation in deep learning and computer vision Ability to bridge technical and medical domains Publication track record in relevant conferences and journals Effective collaboration with interdisciplinary teams

Market Demand

High demand with growing opportunities in both academic and industry settings for biomedical AI specialists

Important Skills

Critical Skills

Deep learning expertise particularly in computer vision applications Programming proficiency in Python and major ML frameworks Strong mathematical foundation for algorithm development Communication skills for cross-disciplinary collaboration

Beneficial Skills

Medical or biological background Experience with medical imaging standards Knowledge of medical workflows and clinical validation processes Project management capabilities

Unique Aspects

Integration with bAIome center provides unique opportunities for AI-clinical collaboration
Access to extensive medical imaging datasets and clinical expertise
Strong institutional support for translational research
International research environment with diverse collaboration opportunities

Career Growth

3-4 years for PhD completion with potential postdoctoral opportunities

Potential Next Roles

Senior Research Scientist Principal Investigator Industry Research Lead Medical AI Consultant

Company Overview

Universitätsklinikum Hamburg-Eppendorf (UKE)

UKE is one of Germany's leading university hospitals with over 15,300 employees and significant research funding

Top-tier academic medical center with strong research infrastructure and international collaborations
Major healthcare and research hub in northern Germany with extensive regional partnerships
Academic environment with emphasis on innovation, collaboration, and work-life balance
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