Post-doctoral discovery data sciences: machine learning for small molecule design and synthesis

Job description

Job Description

Requisition ID: 1805674790W

Within the Discovery Sciences group, which provides advanced technology support to drug discovery projects in Janssen, the Computational Sciences department is responsible for comprehensive analyses of high-dimensional datasets and MultiTask and DeepLearning machine learning applied to small molecule programs. The position will be opened on the Beerse campus, which is the flagship R&D center for small molecules within Janssen, investing over 1 billion euros each year in R&D.

Activities cover the integration of information from the broadest possible spectrum of datasources (chemical structure, microscopy images and omics, …) to comprehensively infer biological activities of millions of chemical compounds, and to apply these predictions to inform projects. In addition, the team designs and supports the creation and application of deep learning and generative approaches for suggesting novel compounds to make, as well as the creation and application of deep learning methods for retrosynthesis and forward synthesis approaches. Janssen is looking for a candidate who can interact with medicinal chemists to discuss novel compound suggestions to be synthesized, as well as improve the deep learning approaches to reflect a medicinal chemistry test and design cycle more smoothly.

Job description

In the context of the latter task, the department is opening a position for a post-doctoral fellow data sciences and machine learning for molecule design and synthesis who will focus on the creation and application of deep learning approaches to inform medical chemistry projects. The post-doctoral fellow will do world-class research in generative approaches for suggesting novel compounds to make, as well as the creation and application of deep learning methods for retrosynthesis and forward synthesis approaches.
This will also include the incorporation of high-dimensional datasets to identify interventional strategies for neurological, cardiovascular and metabolic, infectious, immunological or oncological diseases. The candidate will be responsible for

·  the translation of questions of disease experts in the therapeutic areas and wet lab colleagues, to a quantitative analysis formulation
·  the design and execution of deep learning generative approaches to produce actionable conclusions and to inform decision making
·  the design and execution of deep learning retrosynthesis in relation to reaction databases to produce actionable conclusions and to inform decision making
·  the investigation and normalization of reaction databases and vendor building block libraries to be utilized for the above deep learning approaches and scientific collaboration projects with additional commercial and academic partners.
·  work closely together with medicinal chemistry colleagues on disease area projects that result in impact within the project teams, as well as an improvement of the various deep learning modules
·  work with informatics and statistics colleagues to offer the resulting analysis and visualization solutions to the project teams
·  contributing to the scientific weight of the department by authoring peer-reviewed papers and presenting at relevant conferences

Desired profile

Qualifications

·  PhD in machine learning with Master level training in organic chemistry, of PhD in organic chemistry with master level training in machine learning or interdisciplinary training in related quantitative fields with direct exposure to chemical synthesis (ideally a few years of post-doctoral experience in an academic or industrial setting)
·  demonstrated experience with organic chemistry or medicinal chemistry, to drug design hit generation, lead optimization, or ADMETox optimization of small molecules, with a hypothesis driven experimental or clinical follow-up
·  advanced programming and scripting skills that enable the development of functional prototypes
·  experience with DeepLearning machine learning frameworks, like PyTorch, Keras, Tensorflow
·  experience with chemical reaction databases
·  excellent communication, reporting and team interaction skills, self-motivation, proactivity and the ability to work independently

What's in it for you…?
“Caring for the world, one person at a time…”
As an employee we consider you as our most valuable asset. We take your career seriously.
As part of a global team in an innovative environment your development is key and our day-to-day responsibility.
Through e-university, on the job training, various projects and programs, we ensure your personal growth.
Our benefits make sure we care for you and your family now and in the future.
Primary Location
Belgium-Antwerp-Beerse
Organization
Janssen Pharmaceutica N.V. (7555)
Job Function
R&D
Requisition ID
1805674790W