In your role you will work with computational biologists and bioinformaticians to develop AI methodologies in understanding disease biology and discovering drug targets. This role requires strong deep learning expertise and excellent capacity to learn biomedical domain knowledge.

● Partner with computational biologists and bioinformaticians to develop novel computational methods to infer causality in disease onset and progression.
● Develop deep learning methods for analyzing single-cell omics data, biological pathways and molecular networks to identify disease-driving cell types, pathways, and genes.
● Apply natural language processing (NLP) AI in biomedical literature analysis to extract relationships among proteins, genes, drugs, and phenotypes.
● Collaborate with computational biologists to propose drug targets based on deep insights derived from data.

Requirements:
● You have a Ph.D. or M.S. degree in machine learning, computer science, mathematics, physics, computational biology, or a relevant field. Additionally you bring the following characteristics:
● Passion for applying AI to drug discovery and learning biomedical domain knowledge.
● Strong expertise in deep learning model development, including graph neural networks and recurrent neural networks.
● Excellent analytical and mathematical capabilities, being able to identify key questions and come up with innovative mathematical solutions.
● Experience in applying AI to analysis of omics data or biomedical literature is a plus.

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