UD

Research Associate (m/f/d) at Else Kröner Fresenius-Zentrum

DresdenFull-timeOn site2 weeks ago
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Research Associate (m/f/d) in the field of Efficient AI for Computational Pathology

at Else Kröner Fresenius-Zentrum

The position is available from November 1st, 2026, full-time and initially limited to 24 months, with the possibility of extension and longer-term collaboration.

Remuneration is based on the provisions of the collective agreement for the public service of the German federal states (TV-L) and, subject to the relevant personal qualifications, may be classified at pay grade E13.

The position is part of the research project “MedSecureAI – Certifiable Chip Platform for Secure AI Accelerator Integration in Image-Based Medical Detection.” The project is part of the SEMECO Future Cluster and combines research in medical AI, digital pathology, edge computing, and trustworthy hardware platforms.

The aim of the project is to develop and validate a modular, secure, and resource-efficient platform for AI-assisted medical image analysis.

In the medical use case, AI models for digital pathology will initially be trained on high-performance GPU infrastructure and subsequently optimized for local execution at the microscope on resource-constrained edge hardware.

A demonstrator will enable direct and explainable analysis of histological image data at the microscope.

The successful candidate will work in an interdisciplinary and international research environment in the research group of Marco Gustav, PhD, at the Else Kröner Fresenius Center for Digital Health at TU Dresden, and will collaborate closely with academic institutions and industry partners.

The group develops practical AI solutions for challenges in clinical care.

A particular focus is on efficient, locally deployable AI methods for pathology and their clinically relevant application.

Your responsibilities:

Identification, selection, and preparation of suitable histological image datasets for the development and validation of AI models
Development, implementation, and optimization of deep-learning models for histological image data using PyTorch
Design and implementation of efficient data and training pipelines, including data loading, preprocessing, and training
Optimization and porting of the developed models to the target hardware, particularly with regard to computational and memory efficiency as well as inference speed, taking edge AI approaches into account and working closely with the technical project partners
Development and validation of a demonstrator for local AI-assisted analysis of histological image data at the microscope
Scientific analysis, documentation, and publication of research results in peer-reviewed journals, as well as presentation at scientific conferences

🎯Your profile

Completed university degree in Computer Science, Artificial Intelligence, Engineering, Data Science, or a related field
Strong programming skills in Python and PyTorch, as well as very good knowledge of deep learning
Experience in AI-assisted analysis of histological image data
Experience in optimizing AI models under hardware and resource constraints, e.g., through quantization or model compression, as well as experience in explainable AI, is an advantage
Experience with hardware integration or the development of technical systems, ideally in microscopy or imaging, is an advantage
Interest in interdisciplinary research at the intersection of AI, software, hardware, and medicine
Very good English language skills, as well as a structured and team-oriented approach to work

We offer:

Compensation: Based on the TV-L collective bargaining agreement in pay grade E13, plus an annual bonus, provided you meet the personal requirements
Vacation: 30 days of paid vacation
Professional Development: Extensive internal and external training and development opportunities to continuously strengthen your skills
Company Culture: We value transparency, team spirit, and shared success. Celebrate with us at company gatherings or sporting events like the Rewe Team Challenge
Mobility: A subsidy for a job ticket to make your commute eco-friendly and convenient
Health: We promote your well-being with modern fitness and exercise programs at our health center, mental health programs, and a comprehensive workplace health management program
Shopping benefits: Take advantage of employee discounts at our clinic pharmacy, exclusive corporate benefits, and other shopping portals
Work-life balance: Our Family Office supports you with questions regarding daycare spots, vacation programs, and caring for family members. We also offer flexible work arrangements

Your contact in the HR Directorate

Elena Koch

Tel: 0351-458- 2594

Job overview

Posted
26 September 2026
Location
Dresden
Employment type
Full-time
Work model
On site

Company

UD

Universitätsklinikum Carl Gustav Carus Dresden

Dresden
View company profile
Source

This job listing comes directly from the employer’s career site and is hosted there.

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