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Postdoctoral Scientist, Deep Learning / Machine Learning – Drug Discovery - 2406211262W

Description

Johnson & Johnson Innovative Medicine is currently seeking a Postdoctoral Scientist, Deep Learning / Machine Learning to join our In Silico Drug Discovery team. The primary and preferred location is Cambridge, MA. Remote work options in the US may be considered on a case-by-case basis.

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/.

For more than 130 years, diversity, equity & inclusion (DEI) has been a part of our cultural fabric at Johnson & Johnson and woven into how we do business every day. Rooted in Our Credo, the values of DEI fuel our pursuit to create a healthier, more equitable world. Our diverse workforce and culture of belonging accelerate innovation to solve the world’s most pressing healthcare challenges.

We know that the success of our business – and our ability to deliver meaningful solutions – depends on how well we understand and meet the diverse needs of the communities we serve. Which is why we foster a culture of inclusion and belonging where all perspectives, abilities and experiences are valued and our people can reach their potential.

At Johnson & Johnson, we all belong.

Are you an expert in Deep Learning and have a passion to transform Drug Discovery? Within the Drug Discovery Data Sciences organization of Johnson & Johnson Innovative Medicine we have a 2-year position for a Postdoctoral Scientist that will join the In-Silico Drug 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 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.

Key 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

• PhD in machine learning, computer science, applied mathematics or relevant field (completed within the last 2 years, or expected to be completed in 2024) is required.

• Publications at top-tier Machine Learning conferences (i.e., NeurIPS, ICML, ICLR) are strongly preferred.

• Experience developing Deep Learning methods to train graph neural networks is preferred.

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

• Demonstrable expertise with Deep Learning frameworks, like PyTorch, Keras, Tensorflow is required.

• Demonstrable expertise in work with large datasets is required.

• Expertise in GPU computing is required.

• Ability to present and communicate with stakeholders is required.

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

• 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 on the basis of disability. The anticipated base pay for this position is $95,000. The compensation and benefits information set forth in this posting applies to candidates hired in the United States. Candidates hired outside the United States will be eligible for compensation and benefits in accordance with their local market. The Company maintains highly competitive, performance-based compensation programs. Under current guidelines, this position is eligible for an annual performance bonus in accordance with the terms of the applicable plan. The annual performance bonus is a cash bonus intended to provide an incentive to achieve annual targeted results by rewarding for individual and the corporation’s performance over a calendar/performance year. Bonuses are awarded at the Company’s discretion on an individual basis.

Employees and/or eligible dependents may be eligible to participate in the following Company sponsored employee benefit programs: medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance. Employees may be eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).

Employees are eligible for the following time off benefits:

• Vacation – up to 120 hours per calendar year

• Sick time - up to 40 hours per calendar year; for employees who reside in the State of Washington – up to 56 hours per calendar year

• Holiday pay, including Floating Holidays – up to 13 days per calendar year

• Work, Personal and Family Time - up to 40 hours per calendar year

For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits. For more information on how we support the whole health of our employees throughout their wellness, career and life journey, please visit www.careers.jnj.com.

https://www.careers.jnj.com/data-science

Primary Location NA-US-Massachusetts-Cambridge

Other Locations NA-United States, NA-US-Pennsylvania-Spring House, NA-US-California-La Jolla

Organization Janssen Research & Development, LLC (6084)

Job Function Post Doc - R&D Product Development

Req ID: 2406211262W