Jobs

Are you fascinated by how the nervous system and immune system conspire to shape tumor behavior? Do you want to uncover how nerve–immune–cancer cell interactions determine resistance to immunotherapy, including the CAR-T cells? Join our team at the Ertürk Lab as a PhD student and work at the interface of cancer biology, whole-body imaging, spatial proteomics, and AI.

What You Will Do:

• Perform advanced tissue clearing and light-sheet microscopy to map the distribution of micrometastases and their innervation patterns across the whole mouse body at single-cell resolution.
• Use wildDISCO and related whole-body immunolabeling approaches to visualize the engagement of metastases by natural and engineered immune cell populations
• Investigate how spatial relationships between nerves, immune cells, and tumor cells determine sensitivity to immunotherapy, including immune checkpoint blockade and engineered immune cells such as CAR-T cells.
• Apply and adapt AI-based analysis tools for 3D image registration, cell detection, and quantification of nerve–immune–cancer interactions across large-scale whole-body datasets.
• Use 3D spatial omics to characterize the cellular and molecular composition and architecture of the metastatic TME across different conditions.
• Collaborate with cancer biologists, immunologists, neuroscientists, and AI scientists to integrate imaging, molecular, and functional data into a coherent picture of how neural signaling contributes to immunotherapy resistance in metastatic cancer.
• Publish your work in high-impact journals and present at international conferences.

What We Offer:

• State-of-the-art platforms for whole-body tissue clearing, light-sheet microscopy, spatial proteomics, and large-scale computational analysis.
• A highly interdisciplinary and international environment combining cancer biology, neuroimmunology, AI, and systems biology.
• Close collaborations with leading scientists worldwide, including experts in CAR-T cell therapy and caner metastasis.
• Access to our unique whole-body imaging pipelines.
• Mentoring and career development toward both academic and industry paths.

Your Profile:

• Master’s degree in cancer biology, immunology, neuroscience, biomedical sciences, biomedical engineering, or a related field.
• Strong interest in the interplay between the nervous system, immune cells, and tumor cells in a metastatic setting.
• Practical experience in tumor models, immune cell engineering or cancer biology
• Experience in one of the following is a plus: microscopy, tissue processing, work with live animals, programming (e.g. Python, MATLAB), machine learning, or spatial data analysis.
• Curious, proactive mindset and willingness to learn new experimental and computational methods.
• Good communication skills and a collaborative working style in an interdisciplinary team.

Join Us:

Be part of our team to explore how nerves and immune cells — including next-generation engineered effectors such as CAR-T cells — interact within the metastatic tumor microenvironment, and how these interactions can be targeted to overcome immunotherapy resistance.

Please send your application to Xiaoshan Hu (xiaoshan.hu@helmholtz-munich.de). Please include a motivation letter detailing your suitability for the position and relevant prior experiences, a CV and the contact details of 2-3 references in a single pdf file (<2 Mb, do not include transcripts or other supporting documents at this time).

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