Jobs
Principal / Lead Computational Biologist - NLP
Your new company
You will be joining a highly innovative biotech in London developing novel drugs across a range of disease areas as they go into their next phase of growth.
This company has a proprietary platform that integrates a range of algorithms and target identification tools to find and validate drug targets and is looking to add an experienced computational biologist with deep expertise of ML / AI approaches to their well-established team to help progress their pipeline.
They have a highly collaborative and social atmosphere, with a mix of experience and backgrounds and a great working atmosphere in highly modern offices.
Your new role
You will play a leading role in the development and validation of the company's computational platform, working with a number of internal stakeholders and senior management to drive both technical/computational and drug discovery projects forward.
You will manage and conduct projects to support drug discovery efforts by developing and implementing additional functionality/capabilities for the existing platform and coming up with entirely new tools & approaches; primarily within NLP / LLMs, though this is not exclusive.
A key part of this role is to interact closely with the biology, chemistry, business analytics and bioinformatics / computational biology teams to understand requirements and then design new or refine existing platforms to support their work.
There will be plenty of support from the wider team but the expectation is you will act as a technical expert/lead and have significant input into the technical details.
Depending on the level of applicants, this role can be at Principal or Associate Director level, with line management duties for more senior candidates if that is of interest. The role can also stay as an individual contributor if preferred.
What you'll need to succeed
Aside from the ability to work both independently and as part of a wider team, you should ideally have:
- An MSc / PhD (or equivalent experience) in maths, biology, bioinformatics, physics, statistics, data science or a related subject.
Candidates without a higher degree but with a strong background in the utilisation/application of AI within the biotech/pharma industry are also encouraged to apply. - Hands-on expertise of designing, managing and delivering computational projects within a biotech / pharma / drug discovery setting
- The ability to analyse large scale biological (preferably genetic/genomic) data sets
- Strong programming skills in Python and/or R, C++, Java or similar, eg for developing tools, packages, models, algorithms or similar, coupled with a knowledge of good software development practices, eg version control, DevOps, etc
- Experience of working closely with cross-disciplinary teams to understand requirements and translate these into workflows / tools
- A track record of applying Machine Learning or Deep learning approaches to problems, with a good understanding of NLP / Large Language Models and libraries such as TensorFlow, Keras, etc
- Good communication and interpersonal skills
- A real interest in solving technical problems
For more senior candidates, a track record of leadership - either from direct line management or matrix management - of teams is required.
What you'll get in return
You will have the opportunity to make a significant impact on the business, working on cutting-edge projects that aim to improve the lives of millions of people and ultimately help drive a new approach to drug discovery.
You will also get the chance to grow your skills and career in a supportive and collaborative environment that values innovation, creativity and excellence and is highly mission driven.
On top of this, they have a great, modern office facility in London with state-of-the-art equipment and resources.
What you need to do now
If you are interested in this role, please apply online with your CV. If this job isn't quite right for you, but you are looking for a new job in computational biology, please contact me for a confidential discussion.
Keywords: computational, biologist, drug, discovery, deep, machine, learning, LLM, NLP, transformer, AI, ML, DL, network, graph, model, development, biology, London, biotech, Python, R, data, engineering, integration, target, identification, validation, TensorFlow, Keras, neural, net, CNN, biostatistics, biophysics, science, systems, bioinformatics, multi-omics, pharmaceutical, therapeutics
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