A central goal of the internship will be to answer a key scientific and product question: do the microscopy images generated in our lab provide predictive power beyond existing modalities such as omics, clinical, and experimental data?

Key Responsibilities

• Integrate imaging data into existing experimental and ML workflows , ensuring smooth ingestion, preprocessing, and alignment with current datasets and pipelines.
• Develop computer vision feature extraction pipelines to generate predictive representations from images (e.g., segmentation, morphological descriptors, embeddings, and learned features).
• Quantify the added predictive value of imaging features beyond existing modalities (screening, clinical, omics), using rigorous evaluation frameworks, ablation studies, and appropriate performance metrics.
• Perform model debugging and error analysis to understand failure modes, improve robustness, and validate biological/experimental relevance of extracted features.

Minimum Qualifications

• BSc, MSc, MEng, or equivalent degree in statistics, machine learning, data science, or a related field.
• Strong computer vision + deep learning fundamentals (segmentation, object detection, classification, metric learning/embeddings)
• Prior professional experience using Python, with familiarity with modern development tools and environments (GitHub, AWS/GCP).
• Hands-on, curious, and autonomous, with the ability to navigate fast-paced and ambiguous environments.
• Genuine interest in the intersection of data and biology.
• Proficiency in English.

Preferred Qualifications

• Experience with data pipelines, ETL processes, or workflow orchestration frameworks (Airflow, Prefect, or similar).
• Proficiency with data visualization or dashboarding tools (e.g., matplotlib, Plotly, Streamlit, Dash).
• Prior exposure to biological, experimental, or multimodal data.

HR Call (15 minutes) – An initial conversation to better understand your background, experiences, and motivations.

Technical Interview (45 minutes) – A deep dive into your technical skills and hands-on expertise relevant to the role.

On-site Interview – As the final step of our recruitment process, you will visit our office and lab, and work on a concrete case study combining experimental imaging data and computer vision .