Description

Architect and build AI-driven data ecosystems for drug target discovery.

This role is on-site.

Responsibilities

• Architect AI-driven data ecosystems for efficient drug target discovery.
• Implement scalable machine learning models and pipelines for genomic, transcriptomic, and imaging datasets.
• Deploy machine learning solutions and manage large-scale data storage and computation on cloud platforms.
• Apply deep neural networks and advanced AI techniques to extract insights from diverse biological data.
• Collaborate with interdisciplinary teams to translate experimental data into drug discovery strategies.

Required Skills

• PhD in Computer Science, Bioinformatics, Statistics, or a related quantitative field.
• 5+ years of experience in software engineering or data science roles.
• Proficiency in Python and R.
• Experience developing and deploying applications in a cloud environment.
• Proven ability handling complex biological datasets, including consortium and atlas-type data.
• Experience applying advanced statistical and machine learning methods to biological problems.
• Solid experience with AI and machine learning tools and frameworks.

Preferred Skills

• Experience in data harmonization, normalization, and preprocessing of large-scale biological datasets.
• Expertise in genetic algorithms, ensemble methods, and unsupervised learning.
• Deep understanding of the nuances, limitations, and pitfalls of biological datasets.

Key Skills

Education

Any Graduate