Phd Candidate in Machine Learning of Large-scale in Vivo Perturbational Omics

il y a 24 heures

Gent, Belgique VIB Temps plein

**Description**:
**Research Project**:
In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from _in vivo_ perturbational omics data. We have developed _in vivo_ single-cell CRISPR technologies to screen for dozens of molecular factors _in vivo_ during developmental and disease. These technologies are a game-changer in the speed, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine. Extracting this information is still a challenge though, given its intrinsic multidimensional nature (time, perturbation, tissue position, cell state, statistical power).

With modern probabilistic modelling, that combines diffusion and transformer models, there are clear indications that the analysis of this data can be automated. This will open new avenues in data interpretation and building predictive models. Ultimately, the goal is to move towards an active-learning-based screening to unravel particular developmental and disease states in its entirety. The automated analysis of this data will be a key building block within this process.

**Profile**:

- Master’s in software engineering, computer science, data science, bioengineering, bioinformatics, engineering, physics or related
- Experience in either machine learning or computational biology. Interest in both.
- Programming experience in Python.
- Excellent communication skills and fluency in English.
- Collaborative personality with attention for detail.

**Bonus but not required**:

- Experience with training and validating Pytorch and/or JAX deep learning models.
- Experience in single-cell or spatial omics data analysis.

**What we offer**:

- Embedding within a computational team, with extensive experience in computational biology and machine learning.
- Competitive salary and full benefits.
- Access to state-of-the-art computing infrastructure.

**Want to apply?**:

- Motivation letter of 1-1.5 pages
- Curriculum vitae
- University degree certificates

**Diversity & Inclusion**:
By embracing the unique perspectives and experiences of our team members, we aim to foster innovation and advance excellence in research. We believe that a diverse and inclusive workplace is essential for scientific creativity, effective collaboration, and impactful discovery.

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