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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # SynthImmune Research Data Scientist/Research Data Manager - **Company:** Uni Heidelberg - **Location:** Eberbach, Germany - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Big Data, Bioinformatics, Cloud Database, Computational Biology, Image Analysis, Data Integration, Interoperability, Python (Programming Language), Tensorflow, Scientific Computating, Workflow Management Systems, Pytorch, Deep Learning, Convolutional Neural Networks, Jupyter, Information Technology, Data Management - **Published:** September 18, 2026 - **Apply:** https://adb.zuv.uni-heidelberg.de/info/INFO_FDB%24.startup?MODUL=LS&SESSID=0&M1=1&M2=0&M3=0&PRO=40410 ## About the Role * PhD in any field with 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 Application: If you are excited about contributing to cutting-edge research at the interface of bioimaging, data science, and synthetic immunology, we would be delighted to hear from you. Applications should be submitted as a single PDF file including: * PhD transcript/certificate * A letter of motivation ## Description * 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 ## Related Videos - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Kubernetes dev is fun, but setup and ops isn't! 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