Job Detail

PostDoc (Artificial intelligence in de novo molecular design) - (STE00004) 

Description

 

Role Purpose

 

This is a 2 year fixed term Postdoctoral fellowship contract in our Chemistry department where you will have the opportunity to develop new skills while working at the cutting edge of science and innovation. At Syngenta, our work matters; we are looking for the talents of today and tomorrow. 

We are seeking a highly motivated computational scientist to develop and apply state-of-the-art machine learning techniques (including classification, generative modelling, and reinforcement learning) to design new Active Ingredients with a balanced activity/safety profile.

Please provide a Research Summary of 2-5 pages including relevant programming experiences.

 

Accountabilities

• Design and implement Artificial Intelligence methods and apply them to the design of novel Active Ingredients


• Apply productive modelling and generative systems to projects


• Actively support the development of AI strategy in Chemical Research through: prototyping, evaluation of external solutions, intelligence on competitor and potential partners

 

Qualifications

 

Qualifications

• PhD in computer science, statistics, computational chemistry or related field


• Good knowledge of English language (written and spoken)


• Ability to interact in multidisciplinary teams


• Proven organizational skills

Required skills

• Good knowledge in machine learning (especially deep learning) and the typical frameworks (TensorFlow, PyTorch, DeepChem, etc)


• Experience in the development and usage of generative models (variational autoencoders, generative adversarial nets and beyond)


• Good understanding of constrained optimization problems in highly-dimensional space


• Good skills in data analysis and statistics


• Solid background in programming (Python, C++ or Java), good knowledge on LINUX operating system as well as informatics: best practices in programming (versioning, debugging, profiling etc.) with an eye on performance and scalability


• Ability to connect and explore large datasets, build and test predictive models using ML techniques


• Solid understanding of High-Performance Parallel and Distributing Computing, GPU-computing


• Basic knowledge on Database structures


• Basic knowledge of chemoinformatics methods and tools (RDKit)

  

Primary Location

: CHE-Stein-Stein 

Job

: Chemistry