#1 Mon Sep 24, 2018 5:33 pm
Registered: Sep 2018
GTN - A Quantum Leap in Drug Discovery.
Bringing a single new drug to the market costs $2.9bn and takes 15 years, with a high chance of failure. At GTN we combine machine learning and quantum physics, using our unique patent-pending technology, Generative Tensorial Networks, to efficiently access the full drug-like space, i.e. 10^60, and to more accurately predict chemical activities. This has the potential to create substantial efficiencies in the whole drug development cycle which could have a huge positive impact on lives globally.
GTN is well funded by Tier-1 VCs and has built an outstanding interdisciplinary team, a world-class board of advisors and collaborations with a number of global pharmaceutical companies and world-leading research institutes.
GTN received the CogX UK Rising Star award for Outstanding Achievement in Machine Learning handed to us by the British Prime Minister, Theresa May and was recently featured in WIRED Magazine.
We are looking for an outstanding computational chemist with an adaptable and productive working style which would fit in a fast-moving biotech startup.
As part of the role you will:
- Help define the strategy and deliver the pipeline for FEP/TI augmentation of data.
- Help refine the machine learning model output in reference to docking.
- Work with the engineering team to define infrastructure and engineering needs for computational calculations.
- Incorporate ideas from the current literature approaches into structure-based drug design.
- Rapidly gain a high-level understanding of and assimilate other disciplines within the team including machine learning and quantum physics.
As part of an ambitious, fast-paced and interdisciplinary team working on tough but impactful challenges, you can expect to work in a collaborative and intellectually fulfilling environment, working on problems that really matter.
- Challenge the norm.
- Agile, pragmatic perseverance.
- Approachable and supportive people.
- Evidenced impact orientation.
- Personal growth.
What we expect:
- Experience with protein and ligand structure-based model building.
- Experience with molecular dynamics and free energy perturbation calculations, ideally applied to pharma problems.
- A Ph.D. in a related field with some pharma/CRO/Biotech experience (will consider significant experience in lieu of a Ph.D.)
- Experience delivering results and problem solving in pharma programmes.
- An understanding of the drug discovery process.
- Experience in bioinformatics/cheminformatics ie. (docking, QSAR/homology model building, protein homologue building).
- A desire to work with on difficult problems that can have a real impact on the world.
- Talented, motivated and interesting co-workers.
- Intellectual challenge solving meaningful problems.
- A dedicated package for publishing, patenting and attending conferences.
- Budget to buy the IT set-up you need.
- Competitive compensation including meaningful equity ownership.
Apply online at http://gtn.ai/ComputationalChemist.html or email Careers@gtn.ai with any questions.