Postdoctoral Scholar - AI/ML for Drug Metabolite Prediction

5w1 month ago

Johnson & Johnson

Turnhout, BE · Full-time · €60,000 – €96,255

About this role

Johnson & Johnson is seeking a highly motivated postdoctoral scholar for a two-year contract to develop an AI/ML-driven platform for predicting drug metabolites, pharmacokinetics, and molecular properties. This role will facilitate LC-MS-based structure elucidation and compound purification within the Drug Discovery Data Science team.

The candidate will conduct fundamental research, making use of extensive internal biochemical and analytical datasets. This work will result in meaningful and transformative impacts on ongoing drug discovery and development projects by applying the tools developed.

Given the multidisciplinary nature of the project, the candidate will collaborate with a diverse group of drug discovery and development experts along with data scientists. The role involves developing explainable AI tools with aspects of uncertainty estimation and active learning approaches while leveraging a cutting-edge molecular AI architecture.

A successful candidate should demonstrate a strong capacity to build, evaluate, and benchmark deep learning methods and communicate findings in peer reviewed publications. They should be an effective communicator and be comfortable leveraging a large internal network for the purpose of data curation and generation.

Requirements

Strong background and practical experience in applying machine learning and deep learning methods
Experience building, evaluating, and benchmarking deep learning methods
Ability to communicate findings in peer reviewed publications
Comfortable leveraging a large internal network for data curation and generation
Effective communicator in a multidisciplinary team environment
PhD degree in Computational chemistry, Cheminformatics, Physical Chemistry, Analytical Chemistry, Machine Learning, Data Science or a related field

Responsibilities

Design, development, and evaluation of models for analytical instrumentation, metabolite prediction, and PK/PD
Leverage public data and our internal network for the creation and curation of relevant data
Deploy and apply models in an industrial setting
Write peer reviewed publications
Participate in development, training, conferences, internal meetings, and symposia
Develop explainable AI tools with aspects of uncertainty estimation and active learning approaches

Benefits

Two-year postdoctoral contract with a leading healthcare innovation company
Access to extensive internal biochemical and analytical datasets
Opportunity to collaborate with a diverse group of drug discovery and development experts
Exposure to cutting-edge molecular AI architecture and industrial model deployment