SynthImmune Research Data Scientist/Research Data Manager – RDS/RDM (f/m/d)

SynthImmune; Heidelberg; Hybrid; EUR 65,000 - 90,000; Full time

Job summary

SynthImmune invites applications for a Research Data Scientist/Research Data Manager in Heidelberg, affiliated with the IDIP and Heidelberg University. The role focuses on quantitative image analysis, data pipelines, and coordination across imaging, omics and spatial omics datasets.

The successful candidate will implement automated ML workflows, contribute to FAIR data practices, and collaborate with AI groups on campus.

Qualifications

• PhD in a field with a strong bioimage analysis component, computer science, data science, computational biology, or related field
• Several years of relevant professional experience in a research environment
• Strong programming and data analysis skills, with demonstrated expertise in Python and scientific computing ecosystems
• Proven experience in developing and applying deep learning methods for image analysis (CNNs)
• Practical experience with deep learning frameworks (PyTorch, TensorFlow) and model training on large datasets
• Experience with bioimage analysis tools/environments (FIJI/ImageJ, Jupyter, CellProfiler, Napari)
• Experience in developing automated, scalable, reproducible data analysis pipelines
• Experience with research data management and FAIR data principles is an asset
• Collaborative mindset with ability to manage multiple projects
• Excellent communication of complex concepts, training and teaching experience
• Familiarity with multimodal data integration and HPC/cloud processing
• Experience with workflow systems (Nextflow) and large-scale data handling
• Hands-on with advanced microscopy (confocal, light-sheet, super-resolution)
• Experience in core facilities or shared infrastructures
• BSL-2/3 related biosafety exposure optional

Responsibilities

• Design, implement and refine automated image analysis workflows, including ML-based segmentation and feature extraction
• Collaborate with experimental scientists to develop scalable data pipelines and toolsets for diverse microscopy projects
• Serve as main contact for planning and advising on image analysis within IDIP and SynthImmune
• Co-develop innovative computational approaches with AI research groups
• Lead data management practices across the SynthImmune consortium for standardization
• Ensure compliance with FAIR data principles with IT teams
• Foster interdisciplinary collaboration across biology, bioinformatics and data science
• Train and support scientists in coding, workflows and image analysis best practices

Skills

Python

PyTorch

TensorFlow

Machine learning

Bioimage analysis

HPC

Jupyter

ImageJ/FIJI

Napari

Big data

Education

PhD in bioimage analysis or related field

Tools

FIJI/ImageJ

Jupyter

CellProfiler

Napari

Nextflow

CUDA

Git

Job description

The SynthImmune Research Data Scientist/Research Data Manager will be also associated with the Research Data Unit of Heidelberg University . SynthImmune brings together leading researchers to pioneer the emerging field of synthetic immunology, aiming to develop transformative strategies to combat infectious diseases and cancer by understanding and engineering elite immune responses.

Within this collaborative framework, IDIP provides state-of-the-art high-containment microscopy infrastructure (BSL-2 and BSL-3) and advanced imaging technologies spanning molecular to whole-organism scales. The successful candidate will contribute to cutting-edge research at the interface of bioimaging, data science, infection biology and immunology, supporting the quantitative analysis of complex biological systems and helping to translate imaging data into new insights for therapeutic innovation.

SynthImmune Research Data Scientist/Research Data Manager – RDS/RDM (f/m/d)

Full-time, TV-L E 13, for a limited time until 31st of December 2032, available immediately

Key Responsibilities:

• Design, implement and refine automated image analysis workflows, including machine learning–based methods for segmentation, feature extraction and multidimensional molecular and morphological feature-based classification in complex datasets
• Collaborate closely with experimental scientists to develop scalable, robust and automated data pipelines and flexible toolsets to support diverse microscopy-based research projects, including the integration of multimodal datasets (e. g., imaging, omics and spatial omics)
• Serve as the primary point of contact for planning, coordinating and advising on image analysis projects within IDIP and the SynthImmune consortium
• Work in close partnership with leading AI-based data analysis research groups on campus to co-develop and implement innovative computational approaches for consortium-wide challenges
• Lead the implementation of data management practices across the SynthImmune consortium, promoting standardization and best practices
• Ensure compliance with FAIR (Findable, Accessible, Interoperable, Reproducible) data principles in collaboration with IT teams
• Foster interdisciplinary collaboration by actively engaging with researchers across biology, bioinformatics and data science
• Train and support scientists in coding, automated workflows and image analysis best practices to build sustainable in-house expertise

Your Profile:

• PhD in any field with a strong bioimage analysis component, computer science, data science, computational biology, or a related field
• Several years of relevant professional experience in a research environment (e. g., academic research group, core facility, company)
• Strong programming and data analysis skills, with demonstrated expertise in Python and scientific computing ecosystems
• Proven experience in developing and applying deep learning methods for image analysis, such as convolutional neural networks (CNNs) for segmentation and classification
• Practical experience with deep learning frameworks (e. g., PyTorch, TensorFlow) and model training, evaluation, and optimization on large-scale datasets
• Experience with bioimage analysis tools and environments (e.g., FIJI/ImageJ, Jupyter, CellProfiler, Napari), and the ability to adapt and extend them for complex workflows
• Experience in developing automated, scalable, and reproducible data analysis pipelines
• Experience with research data management, including handling large datasets and implementing FAIR data principles, is an asset
• Collaboration-oriented mindset with high self-motivation, reliability, and the ability to manage and prioritize multiple projects
• Excellent ability to communicate complex computational and analytical concepts in a clear and accessible manner, particularly in training and teaching contexts
• Strong analytical thinking and creativity in problem-solving
• Familiarity with multimodal data integration (e. g., combining imaging and omics)
• Experience with high-performance computing (HPC) environments and/or cloud-based data processing infrastructures
• Familiarity with workflow management systems (e. g. Nextflow) and workflow orchestration
• Experience with large-scale data handling
• Hands-on experience with advanced light microscopy instrumentation (e.g., confocal, light-sheet, super-resolution microscopy)
• Prior experience working in core facilities or shared research infrastructures
• Exposure to biosafety level environments (BSL-2/3) or infectious disease research settings

The position is remunerated according to TV-L E 13. The position can be filled in part-time.

We offer the opportunity to work in a highly interdisciplinary and collaborative environment at the forefront of infectious disease research and synthetic immunology, with access to state-of-the-art imaging infrastructure and strong connections to leading computational and AI research groups. Join us in shaping innovative approaches to understand and combat infectious diseases and cancer.

Heidelberg University stands for equal opportunities and diversity. Qualified female candidates are especially invited to apply. Persons with severe disabilities will be given preference if they are equally qualified. Information on job advertisements and the collection of personal data is available here .