Description

In this role, you will bridge the gap between data science and biology by using machine learning to uncover patterns in omics data and drive the development of innovative biological solutions.

Requirements

• •MSc or PhD in Data Science, Statistics, Machine Learning, Computational Biology, Bioinformatics, or related field
• •3+ years of machine learning experience with biological, biochemical, environmental, or agricultural datasets
• •Strong understanding of biological data, analysis methods, and multivariate statistics
• •Strong proficiency in Python, R, UNIX/Linux, and ML frameworks
• •Ability to handle large datasets and 'omics data analysis tools
• •Ability to inspire and collaborate in scientific work
• •Passion for innovation and problem-solving in dynamic environments
• •Experience deploying data science solutions cross-functionally

Tasks

• •Identify patterns in product performance
• •Predict outcomes using environmental and phenotypic data
• •Analyze scientific experiments with machine learning
• •Guide the development of novel biological solutions
• •Map the biologicals data landscape and capabilities
• •Deploy analytical methods and multi-omics approaches
• •Evaluate and develop new data analysis tools
• •Validate findings through iterative trial approaches
• •Communicate results to technical and non-technical audiences
• •Curate large-scale omics datasets for biomarker discovery
• •Recommend data collection strategies to ensure integrity
• •Shape the biologicals data analysis strategy
• •Collaborate to deploy innovative digital science approaches
• •Improve predictive model applications with R&D IT
• •Support business users with data management change initiatives

Tools & Technologies

Benefits