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Postdoctoral Fellow – Deep Learning / Machine Learning - 2406194036W

Description

Postdoctoral Fellow – Deep Learning / Machine Learning

Are you an expert in Deep Learning and have a passion to transform Drug Discovery? Within the Drug Discovery data sciences organization of Janssen we have a position for a PostDoc that will join the In-Silico discovery team. The successful candidate will contribute to a cutting-edge project that integrates quantum mechanics (QM) data with deep learning (DL) models to advance molecular predictive modeling. This role involves working closely with experts across various domains to develop innovative methods and tools that will enhance our drug discovery processes.

The position can be based in Beerse, Belgium. Remote work options may be considered on a case-by-case basis and if approved by the company.

The ideal candidate will have a strong background in deep learning and machine learning, with a keen interest in applying these skills to drug discovery. We are looking for a candidate with publications in high-level venues like NeurIPS, ICML, or ICLR with a background in drug discovery, demonstrated software skills, and knowledge of Python, PyTorch, and other DL-related tools. The candidate will be expected to collaborate effectively with cross-functional teams, contribute to the development of state-of-the-art methods, and ensure the reproducibility of experimental results. This is an exciting opportunity to be at the forefront of pharmaceutical innovation, leveraging advanced computational techniques to make a significant impact on healthcare.

Role and responsibilities

• Research and develop deep learning methods to effectively train graph neural networks for Quantum Mechanics and other physics informed data.

• Contribute to the creation of comprehensive reports and scientific publications documenting the methods and results of research projects. Publish findings in high-level conferences and journals.

• Participate in team meetings, brainstorming sessions, and collaborative projects to drive innovation and solve complex problems. Work closely with cross-functional teams, including data scientists, chemists, and biologists, to integrate deep learning models into the drug discovery pipeline.

Qualifications

Requirements

• PhD in machine learning, computer science, applied mathematics or relevant field

• Publications at top-tier Machine Learning conferences (NeurIPS, ICML, ICLR)

• Demonstrable expertise in developing deep neural networks (transformers, Bayesian neural nets, RNN, CNN) is required

• Demonstrable expertise with DeepLearning frameworks, like PyTorch, Keras, Tensorflow

• Demonstrable expertise in work with large datasets

• Expertise in GPU computing

• Ability to present and communicate with stakeholders

• Ability to translate data into information and strategies into executable action plans

• Knowledge in ChemInformatics is desirable

Johnson & Johnson is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against based on disability.

About Johnson & Johnson

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com/.

Primary Location Europe/Middle East/Africa-Belgium-Antwerp-Beerse

Organization Janssen Pharmaceutica N.V. (7555)

Job Function Post Doc - R&D Product Development

Req ID: 2406194036W