AI Scientist – PhD Position Institute for Intelligent Biotechnologies (iBIO), Helmholtz Munich / LMU Munich
We are looking for a PhD student with a strong background in omics data analysis to build AI-driven, whole-body multi-omics atlases of the mammalian organism. The project combines the world’s largest and highest-resolution whole-body 3D imaging datasets with scRNA-seq, spatial transcriptomics, proteomics, and genetic perturbation data to create integrated, cell-level atlases across the entire body.
Project:
You will focus on integrating and modeling:
- Single-cell and single-nucleus RNA-seq
- Spatial transcriptomics
- Proteomics and spatial proteomics
- Genetic perturbation and disease models
- Whole-body, single-cell-resolution 3D imaging data
The goal is to generate unified, AI-driven omics atlases that map every cell type, state, and molecular program across the entire mammalian body, and to make these atlases predictive for disease and therapy response.
Your tasks:
- Analyze and integrate large scRNA-seq and spatial transcriptomics datasets
- Build deep learning models for multimodal omics integration
- Align omics data with 3D whole-body imaging maps
- Create cell-type and cell-state atlases across organs and systems
- Develop models to predict molecular changes under perturbations and therapy
- Work closely with experimental, imaging, and AI teams
Your profile:
- Strong background in computational biology, bioinformatics, systems biology, or related fields
- Hands-on experience with scRNA-seq, spatial transcriptomics, or proteomics analysis
- Experience using deep learning or advanced ML for omics data
- Strong skills in Python, R, and relevant omics toolchains
- Familiarity with Scanpy, Seurat, Bioconductor, or similar frameworks
- Interest in large-scale biological integration and atlas-level biology
- Curious, independent, and comfortable working across disciplines
Supervision & Hiring Team:
- Hiring Manager: Prof. Dr. Ali Ertürk
- AI Team Lead: Dr. Ying Chen
- Hiring Administration: Stefanie Reitinger
What we offer:
- Access to unique whole-body imaging and multi-omics datasets
- Large computing clusters at our Institutions (Dedicated A100 clusters and petabyte-scale storage)
- Work at the interface of AI, omics, and systems biology
- Strong interdisciplinary supervision and collaboration
- International research environment and visibility
- Full PhD position with competitive TV-L salary
Environment:
iBIO at Helmholtz Munich and LMU Munich combines advanced imaging, omics, and AI to build digital, predictive models of mammalian biology, from cell to whole organism.
Application:
Please send:
- CV
- Short motivation letter (max 1 page)
- Academic transcripts
- Links to code, data analysis, or publications (if available)
To:
Stefanie Reitinger, Hiring Administration, iBIO Helmholtz Munich
E-Mail: stefanie.reitinger@helmholtz-munich.de
Applications will be reviewed on a rolling basis until the position is filled.
Staff Scientist – Tissue Clearing & Image Analysis (m/f/d), full-time, ISD/LMU Munich (LMU Klinikum): start 01 January 2026.
- Lead tissue clearing and light-sheet workflows across collaborative projects
- Data analysis + visualization, atlas registration, quantitative readouts
- Methods development and new analysis pipelines with our AI team
- Maintain cutting-edge light-sheet systems (optional: support animal license writing)
- Strong hands-on background in tissue clearing and/or fluorescence microscopy
- Experience with light-sheet microscopy and 3D imaging workflows
- 3D tools (e.g., Imaris and/or arivis Vision4D), stitching (e.g., BigStitcher), and quantitative analysis in cleared tissues
- Service mindset, strong organization, excellent scientific English
We are looking forward to hear from you!
Open position for LMU-CSC scholarship candidates 2026
Department/Institute: Institut für Schlaganfall- und Demenzforschung (ISD)
Subject area: Artificial intelligence, deep learning, image analysis, bioinformatics
Name of supervisor: Ali Ertürk
Number of open positions: 2 Ph.D. in AI and Machine Learning
Project title: Multimodal integration of biomedical data
Project description:
Our group is focused on developing artificial intelligence (AI) tools to analyze large-scale biological imaging data at single-cell resolution and associated molecular data to develop predictive models for diverse biological and medical applications. By combining cutting-edge imaging and computational technologies, we aim to uncover new insights into health, disease, and therapeutic responses.
We uniquely combine whole-body tissue clearing and three-dimensional imaging techniques for entire mice and large human samples with spatial ‘omics and state-of-the-art AI (e.g., Pan…Ertürk, Cell 2019; Zhao…Ertürk, Cell 2020; Bhatia…Ertürk, Cell 2022; Mai…Ertürk, Nature Biotech. 2024; Kaltenecker…Ertürk, Nature Methods 2024, Luo ..Ertürk, Nature Biotech. 2025). Our research interests include mapping health and disease processes across the body, conducting molecular analyses of spatially defined physiological and pathological structures, developing new drug delivery approaches, and creating novel AI tools to better understand mammalian biology.
For the current project, we are seeking two skilled computer/data scientists to advance methods for multimodal integration of molecular and phenotypic data with large-scale, single-cell resolution datasets spanning entire animal models and large human tissues. The goal is to move beyond traditional, annotation-heavy approaches by developing AI systems capable of linking molecular signatures with 3D spatial phenotypes across complex biological samples.
Requirements:
· Strong proficiency in programming environments such as Python or R, and in data visualization approaches
· Experience with machine learning frameworks (e.g., PyTorch, TensorFlow) is an advantage
· Familiarity with bioinformatics, large-scale data analysis, or high-performance computing is a plus
· Please note you need to be a chinese citizen to be eligible for this program
This project seamlessly bridges AI, high-performance computing, and bioinformatics to transform high-resolution imaging data into actionable biological and medical insights.
Project time plan:
Full Doctoral Study-Model: 48 month
Language requirements:
English at least B2 (TOEFL score >80, >25 in the Speaking Section preferred)
Academic requirements:
· Undergraduate degree in computer science or related field.
· Experience in AI-based image analysis or related fields preferred.
· Unfortunately, for administrative reasons we cannot accept students from the following institutions:
• Beihang University (Beijing University of Aeronautics and Astronautics), Beijing
• Beijing Institute of Technology, Beijing
• Harbin Engineering University, Harbin
• Harbin Institute of Technology, Harbin
• Nanjing University of Aeronautics and Astronautics, Nanjing
• Nanjing University of Science and Technology, Nanjing
• Northwestern Polytechnical University, Xi’an
To applicants: Please send following initial application documents to LMU-CSC Office before 15th December:
➢ Resume and Research Motivation Letter
➢ Certificate of Proficiency in English, equivalent to IELTS Test Academic 6.5 (no module below 6) or TOEFL IBT 95, is required
➢ Two letters of recommendation directly sent from your current Supervisors/ Professors to LMU-CSC Office
Contact LMU-CSC Office: csc.international@lmu.de