PhD candidate

**Job Description**
We are seeking a motivated PhD candidate to join a collaborative research program focused on developing probabilistic deep-learning models. This project aims to automatically extract biological and statistical knowledge from in vivo perturbational omics data, utilizing advanced single-cell CRISPR technologies. The goal is to apply modern probabilistic modeling, combining diffusion and transformer models, to automate the analysis of multidimensional data and move towards active-learning-based screening for unraveling developmental and disease states. The candidate will be embedded in both experimental and computational teams, fostering an interdisciplinary environment.

**Skills & Abilities**
• Experience in either machine learning or computational biology, with an interest in both.
• Programming experience in Python.
• Excellent communication skills.
• Fluency in English.
• Collaborative personality with attention for detail.
• Experience with training and validating Pytorch and/or JAX deep learning models (bonus).
• Experience in single-cell or spatial omics data analysis (bonus).

**Qualifications**
Required Degree(s) in:
• Software engineering
• Computer science
• Data science
• Bioengineering
• Bioinformatics
• Engineering
• Physics
• Related fields (Master’s level)

**Experience**
Other:
• Experience in either machine learning or computational biology.
• Programming experience in Python.

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