If you are interested in learning more about the group, we invite you to get in touch.
Charité – Universitätsmedizin Berlin is one of Europe’s largest and most prestigious university hospitals, combining excellent patient care with pioneering biomedical research. At the intersection of medicine, biology, and data science, Charité develops innovative approaches for the precision medicine of tomorrow.
This position is embedded in the newly established Einstein Center for Early Disease Interception (EC-EDI), a consortium of leading Berlin institutions including Charité, the Berlin Institute of Health (BIH), Max Delbrück Center, and TU Berlin. The center’s mission is to diagnose and intercept diseases at their earliest stages – when only a few cells are affected – using cutting-edge single-cell technologies, advanced AI, and patient-derived disease models. The successful candidate will work jointly with two research groups:
As part of the Einstein Center for Early Disease Interception, we are recruiting a PhD student to develop computational methods enabling rapid, data-driven diagnosis of lung diseases.
Our goal is to build an “immune ecotype” framework that transforms single-cell RNA sequencing data from blood samples into interpretable feature vectors, enabling machine learning-based classification of lung diseases including viral and bacterial infections, autoimmune conditions, and lung cancer. We aim to translate these scRNA-seq-derived signatures to ultra-high-plex flow cytometry for clinical deployment.
Your Tasks:
Required:
Desirable:
We are looking for a curious, self-driven individual who enjoys interdisciplinary collaboration and is motivated to translate computational advances into clinical practice.
Please send your motiviation letter, CV (including contacts of ideally two references) and master’s certificate and/or current transcript to lisa.buchauer@charite.de.
We are looking for a student research assistant (studentische Hilfskraft) to join our team starting in February or March 2026 for a period of nine months at 40 hours per month.
We are a computational biology and bioinformatics research group with a focus on single-cell omics data in immunology and infectious diseases (https://buchauer-lab.eu/). This position is part of the newly funded Collaborative Research Center TRR 418 “Foundations of Circadian Medicine.”
The successful candidate will curate, process, and integrate publicly available omics datasets related to circadian rhythms into a database with a web interface that we are currently developing. The primary focus will be on bulk RNA-seq data, though single-cell RNA-seq and proteomics datasets will also be relevant.
We are looking for a reliable, detail-oriented, and self-motivated person who is currently enrolled in a degree program in bioinformatics, computational biology, or a related field. Proficiency in Python or R is required, and prior experience with transcriptomics data analysis is a strong advantage.
The position is based at Campus Virchow-Klinikum.
If you are interested, please send your CV, transcript of records, and a short motivation letter that includes a brief description of one previous bioinformatics project you have worked on to lisa.buchauer@charite.de .
If you are interested in doing any of the above in my lab, I will be happy to hear from you to discuss your interests and currently available project options. Please reach out to me with your CV, your transcript of records as well as one paragraph describing a previous research project of yours, ideally a computational one, at lisa.buchauer@charite.de. For bachelor’s students without prior research experience, it is okay to describe a class project instead.
We are interested in candidates from quantitative backgrounds (physics, mathematics, computer science, computational biology, bioinformatics or similar) with a desire to apply their skills to biomedical research questions. Good command of at least one programming language (e.g. python, R, Julia) is required. Candidates with life science background (biology, biomedicine, biochemistry or similar) are also welcome to apply if they have a strong analytical side and the desire to expand their theoretical and computational skills.
Prior experience with any of the following is considered a plus: omics data analysis, mathematical modeling, machine learning, spatial or temporal data analysis, software development principles and biological wet-lab work. Candidates should be curious, willing to work in a multidisciplinary team, and have a strong sense of ownership for their projects. Fluency in English is required.