Application Guide

How to Apply for PhD student Machine Learning for Immunology

at Charité Center for Global Health

🏢 About Charité Center for Global Health

The Charité Center for Global Health is part of Charité – Universitätsmedizin Berlin, one of Europe's largest university hospitals with a strong international reputation in medical research. This position is embedded within the EC-EDI consortium, offering unique access to large-scale clinical datasets and direct collaboration with leading immunologists and clinicians, bridging computational methods with real-world medical applications.

About This Role

This PhD role focuses on developing machine learning algorithms to integrate single-cell RNA sequencing data from over 1,000 patients, creating interpretable immune signatures for lung disease diagnosis. You'll translate computational findings to spectral flow cytometry measurements, directly impacting multi-class disease classification and collaborating with clinical partners across Europe.

💡 A Day in the Life

A typical day might involve morning meetings with clinical collaborators to discuss data requirements, followed by coding sessions developing batch correction algorithms for newly acquired scRNA-seq datasets. Afternoons could include analyzing immune cell type proportions across patient cohorts, validating ML classifiers, and documenting methods for consortium-wide reproducibility.

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Interview Prep

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🎯 Who Charité Center for Global Health Is Looking For

  • Has a Master's in computational biology/bioinformatics with hands-on experience processing scRNA-seq data using Python/R packages like Scanpy or Seurat
  • Demonstrates practical ML experience with batch correction methods (ComBat, Harmony) and classifier development for high-dimensional biological data
  • Shows ability to work independently on complex data integration problems while maintaining meticulous documentation for reproducibility
  • Possesses basic understanding of immunology concepts (cell types, immune signatures) or strong motivation to learn this domain quickly

📝 Tips for Applying to Charité Center for Global Health

1

Highlight specific experience with batch correction of omics data – mention tools you've used (e.g., Harmony, ComBat, BBKNN) and the scale of datasets processed

2

Include a GitHub link or portfolio with code samples demonstrating scRNA-seq analysis pipelines or ML classifiers applied to biological data

3

Reference the EC-EDI consortium in your application – show awareness of this collaborative network and how your skills would contribute

4

Quantify your programming experience: specify years using Python/R for bioinformatics and mention relevant libraries (scikit-learn, TensorFlow/PyTorch, Bioconductor packages)

5

If you have any experience with flow cytometry data analysis (even basic), emphasize this as it directly relates to the translation aspect of the role

✉️ What to Emphasize in Your Cover Letter

['Explain your motivation for working at the intersection of machine learning and immunology, specifically mentioning lung disease applications', 'Describe a specific project where you developed ML methods for high-dimensional biological data, emphasizing reproducibility and cross-dataset validation', "Demonstrate understanding of the role's translational aspect – how computational findings can impact clinical diagnostics through flow cytometry", "Highlight your ability to collaborate across disciplines, given the role's involvement with clinical and experimental partners"]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Review publications from Charité's immunology and computational biology groups, particularly those involving single-cell genomics or lung disease
  • → Investigate the EC-EDI consortium's research focus and recent publications to understand the broader collaborative context
  • → Explore Charité's specific resources and core facilities for single-cell genomics and flow cytometry available to researchers
  • → Look into Germany's PhD system and funding structures for part-time doctoral positions in academic medicine

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Technical discussion about batch correction strategies for integrating scRNA-seq data from multiple studies with different protocols
2 Walkthrough of your approach to feature engineering for creating stable, interpretable immune signatures across datasets
3 Case study: How would you design an ML pipeline for multi-class lung disease classification using integrated single-cell data?
4 Questions about your experience with version control, reproducible research practices, and documentation for collaborative projects
5 Scenario-based questions about communicating technical findings to non-computational clinical collaborators in the EC-EDI consortium
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⚠️ Common Mistakes to Avoid

  • Submitting generic ML applications without demonstrating specific experience with biological data types (especially single-cell genomics)
  • Failing to show understanding of the translational aspect – treating this as purely a computational role without clinical application context
  • Not providing concrete examples of independent project work or reproducible research practices in your application materials

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

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Good luck with your application to Charité Center for Global Health!

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