Postdoctoral Scholar, AI/ML for drug metabolite prediction and LC-MS analytical chemistry

Johnson & Johnson Innovative Medicine

7d • €60,000 - €96,255 • Hybrid

About The Position

The Drug Discovery Data Science team is seeking a highly motivated postdoctoral scholar for a two-year contract to develop an AI/ML-driven platform for predicting drug metabolites (SOM), pharmacokinetics, and molecular properties facilitating LC-MS-based structure elucidation and compound purification. In this role, the candidate will conduct fundamental research, making use of extensive internal biochemical and analytical datasets. This 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 while 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. Additionally, they should be an effective communicator and be comfortable leveraging a large internal network for the purpose of data curation and generation. The Drug Discovery Data Science team is part of Therapeutics Discovery and brings innovative AI/ML solutions to all steps and areas of the drug discovery process, enabling long-term visionary plans within the company surrounding the new discovery paradigm.

Requirements

• PhD degree in Computational chemistry, Cheminformatics, Physical Chemistry, Analytical Chemistry, Machine Learning, Data Science or a related field
• 0-4 years of related experience
• Strong background and practical experience in applying machine learning and deep learning methods, benchmarking AI models
• Strong background in conventional cheminformatics, respective python packages and software
• General understanding of general, organic, and analytical chemistry
• Strong scientific publication track record (peer reviewed publications, patents, preprints) and/or demonstrated contributions to computer codebases
• Proficiency in Python to the capacity to quickly prepare, analyze, and build models around data
• Highly collaborative, and capable of working with a large internal network to leverage various data sources

Nice To Haves

• Strong understanding of analytical chemistry and chemical instrumentation
• Understanding of drug metabolization and PK/PD
• Modeling experience utilizing uncertainty-aware learning, conformal learning, and active learning
• Application and understanding of modern agentic workflows and LLMs
• Practical understanding of liquid chromatography and mass spectrometry
• Knowledge of modern databases
• Experience with automation and robotization of scientific instruments

Responsibilities

• Design, development, and evaluation of models for analytical instrumentation, metabolite prediction, and PK/PD
• Leveraging public data and our internal network for the creation and curation of relevant data
• Deployment and application of models in an industrial setting
• Writing peer reviewed publications
• Development, training, conferences, internal meetings, and symposia

Benefits

• annual bonus with set target (% of pay) depending on pay grade / location, where the actual amount is based on the employees’ and companies’ performance of the previous calendar year, or sales commissions.
• vacation days
• parental leave for a minimum of 12 weeks
• bereavement leave
• caregiver leave
• volunteer leave
• well-being reimbursement
• programs for financial, physical and mental health
• service anniversary and recognition awards
• insurance plans

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree