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Senior/Principal Scientist, Pharmacology

Rehovot Science Park, Israel · Full-time

About The Position

DeepCure is seeking an exceptional and highly motivated Principal Scientist to join our fast-growing collaborative team. As a Principal Scientist at DeepCure, you will work on the biggest challenges in the pharmaceutical industry, apply cutting-edge technologies, and help us shape the company’s scientific vision. You will work hand-in-hand with other drug discovery scientists and software engineers and be accountable for building and managing a portfolio of biological targets aligned to unmet medical needs that take full advantage of DeepCure’s AI approach. This is a truly unique position in which you will have a leading role in changing the way the industry approaches drug discovery.


 More about DeepCure

DeepCure is a next-generation therapeutics company, built from the ground up with equal importance to computation and life sciences. Our mission is to deliver to patients safer and more efficacious therapeutics that are extremely unlikely to be discovered by traditional drug discovery pipelines. We are a team of curious, multidisciplinary, and impact-driven professionals on a quest to redefine the way drugs are discovered. Our main US office is located in Boston, and our Israel office and lab is located in the Ness Ziona Science Park. This position is based in our Israel office/lab.

Requirements

  • Deep passion for the intersection of multidisciplinary methods and the future of drug discovery, as well as a desire to play a pivotal role in a nascent startup.
  • Ph.D. in Biological Sciences, or related discipline, with at least 5+ years of industry experience, at least 3 of them in a lead discovery role, preferably leading a drug discovery program. Postdoctoral research periods would be considered as relevant experience in case of drug-discovery-related research. 
  • Deep expertise in immunology with a proven track record of scientific accomplishments: peer-reviewed publications and presentations at key scientific conferences.
  • Experience leading an immunology drug discovery program is required; preference will be given to those who have successfully driven a program from the early stage to clinical candidate nomination.
  • A strong molecular and cellular biology background.
  • Deep knowledge of existing/emerging technologies model systems (in vitro, in vivo and ex vivo).
  • Experience with small molecule phenotypic screening.
  • Appreciation of how to utilize big data to drive discovery efforts.
  • Solid understanding of other disciplines that compose a drug discovery team.
  • Extensive experience engaging with CROs to direct, manage, and coordinate external efforts.
  • Demonstrated ability to conceptualize and integrate novel ideas and approaches into program workflows.
  • Ability to work at a fast pace and readily adopt new technologies and ways of thinking.
  • Experience working in cross-functional teams with the ability to effectively convey complex subject matter to non-experts.
  • Excellent communication skills. Ability to communicate in an open, clear, timely and consistent manner.
  • Exceptional scientific record-keeping, organization, and management of data.
  • Ability to work on-site in our office/lab space, and flexibility in work hours in order to accommodate collaboration with our US-based team. 

Hiring level commensurate with experience.

Responsibilities


In this role you will:

  • Function as Program Lead and drive one or more early-stage drug discovery programs from early lead to IND.
  • Work closely and in collaboration with the Director of Biology to help build and expand the current portfolio. 
  • Represent pharmacology on cross-functional and strategic teams, including external collaborations and assess pharmacological aspects in different projects.
  • Provide oversight for work conducted by CRO(s).
  • Act as a mentor to junior researchers 
  • Initiate and engage with researchers and key opinion leaders from industry and academia to establish scientific studies to promote and support DeepCure’s new and ongoing programs.  
  • Facilitate build-up of internal research capabilities in DeepCure wet lab 
  • Support integration of AI and automation into the discovery programs to promote the scientific work


Benefits

For the right candidate, we'll offer a competitive salary and a generous equity grant. Your compensation is rounded out by a strong benefits package:

  • A leadership team that values and prioritizes your professional development
  • Flexible work hours
  • Unlimited paid leave and sick time
  • Lunch subsidies (TenBis)
  • Company contribution toward study fund (keren hishtalmut).
  • Transportation expenses/parking 
  • Work in a cool and vibrant space at the heart of Rehovot Science Park
  • Have the opportunity to work with an international team of innovative scientists across different disciplines. 
  • Work closely with a team of humble, mission-driven professionals, with a trust-based and open communication culture. 
  • A great professional growth potential

“Brainstorming on my challenges with all these amazing brains deserves a shout-out every sprint” (Jon, a member of our Machine learning team).

Most importantly, you'll have a huge impact, do important work, and work with a team of people you'll genuinely enjoy spending the day with.

DeepCure is an equal opportunity employer, dedicated to creating a workplace that is free of harassment and discrimination. We base our employment decisions on business needs, job requirements, and qualifications — that's all. We do not discriminate based on race, gender, religion, health, personal beliefs, age, family or parental status, or any other status. We don't tolerate any kind of discrimination or bias, and we are looking for teammates who feel the same way.

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Molecular Foundry

At DeepCure, automation isn’t just about reducing the cost and time of compound synthesis – it’s about going beyond the limits of manual synthesis to carry innovation all the way through the design-build-test-learn cycle. Our foundry unlocks the chemical space that AI drug design tools want to explore but can’t because it is not practicably available to most chemists. DeepCure’s Molecular Foundry is built to expand the usable chemical space for drug discovery through increased synthesis success rates, removal of human bias in synthesis, and greater efficiency of custom multi-step synthesis.

Automated Synthesis

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MolGen™

Our patent-pending molecular generation tool, MolGen™, designs novel, diverse compounds. Using state-of-the-art deep reinforcement learning (RL), MolGen™ constructs synthesizable compounds with features that capture the important molecular interactions for binding and selectivity, as well as deliver the desired ADME-tox profile of the target candidate profile (TCP).

Multiparameter Optimization

MolGen™ is designed to generate leads, rather than hits, from Day 1, which is made possible by a proprietary set of ADME-tox models (DeepPropR™). The figure shows the accuracy of our 10 most used DeepPropR™ models from a prospective evaluation.

Output of PocketBlueprinter™

MolGen™ – building & iterating compounds

Novel, potent, & selective compound

Hypothesis Generation

Unlike other AI drug discovery companies, DeepCure does not use AI to simply match a library of compounds to a known pocket. Instead, we create causal, data-driven, human-interpretable hypotheses for binding to a given protein target. This enables us to go beyond known binding sites and ligands.

Structure Preparation

We prepare 3D structural models using a combination of publicly available crystal structures, non-public structures, and predicted structures. As part of our proprietary structure preparation protocols, our scientists review a set of data quality metrics for the structures, select reference structures, delete bad structures, and group structures. This ensures the structure(s) used for hypothesis generation is the best representation possible.

PocketBlueprinter

For most therapeutic targets, there is no data, limited data, or biased data. PocketBlueprinter™ allows us to generate novel hypotheses by leveraging AI/ML and computational chemistry methods to map the protein surface and identify novel binding modes. The outputs serve as an initial binding hypothesis for our molecular generation tool, i.e. MolGen™.

Causal Analysis

ML methods for drug discovery typically focus on correlations. However, these methods lead to biases for the types of compounds that have failed in discovery and are inadequate for finding truly novel compounds. To overcome these shortcomings, DeepCure uses causal ML to find binding interactions without the biases for failed binding modes and/or previous compound structures.

Medicinal chemists engage in a conversation with explainable models

DeepCure’s platform is designed to be human-interpretable. Causal features can be shown as heatmaps in 3D (or mapped to 2D) for review by medicinal and computational chemists, enabling identification of irregularities or gaps in the models. By seeing how molecules are predicted to interact with the protein, scientists can make rational design changes to the molecule and explore interesting molecular interactions. Human interpretability allows for a feedback cycle that ensures scientists don’t blindly follow the ML algorithm or chemists’ intuition.