BACKGROUND

RESPONSIBILITIES

• You will lead the machine learning discipline, develop and implement machine learning strategies for target identification
• Work collaboratively with internal drug discovery projects, therapeutic divisions and platform teams, using expertise in machine learning and statistical modelling to address key biological questions and deliver solutions
• Establish and nurture academic collaborations to drive AI/machine learning based genomic research

REQUIREMENTS

• An excellent academic background, with a PhD in Mathematics, Quantitative Biology, Statistics, Computer Science or a related discipline
• Experience managing a multi-disciplinary team of statisticians, data scientists, bioinformaticians etc.
• Experience working with genomic data (NGS, WGS, WES) and image data is ideal
• Experience applying machine learning to target discovery sciences/pre-clinical
• Expertise in one or several of the core machine learning areas, eg. Artificial Neural Networks, Supervised/Unsupervised learning methods, Support Vector Machines, Bayesian approaches, Gaussian processes, Markov Models, Decision Theory etc.
• Strong technical ability, excellent programming skills with expert use of Python sand R, as well as relevant frameworks such as scikit-learn & Tensorflow
• Good understanding of molecular biology, cell biology and genomics

HOW TO APPLY