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Computational Chemist: AstraZeneca Cambridge

We are seeking experienced and knowledgeable computational chemists to join the fast-growing chemistry group within the Oncology medicinal chemistry department. As a computational chemist, you will work collaboratively with medicinal chemists and multidisciplinary teams to design compounds with improved potency, selectivity, activity and/or ADMET properties. By working simultaneously across multiple projects (2-3), in all discovery phases, you will identify and drive ligand design strategies and efficiently and proactively apply a full range of drug design and computational chemistry approaches to tackle complex problems within a project, delivering results to timelines that impact the design of compounds for synthesis and testing. You will contribute to target selection and the initiation and progress of new projects and provide input to open cross-project discussions. Dependent on experience you may function as the lead chemist.—Cambridge/Computational-Chemist_R-067912-1

Posted 8th January 2020

Several Positions: Charles River

For 70 years, Charles River employees have worked together to assist in the discovery, development and safe manufacture of new drug therapies. When you join our family, you will have a significant impact on the health and well-being of people across the globe. Whether your background is in life sciences, finance, IT, sales or another area, your skills will play an important role in the work we perform. In return, we’ll help you build a career that you can feel passionate about.

We have three exciting new opportunities for talented, dynamic Computational Chemists to provide scientific excellence within the CADD team, at our drug discovery facilities in Saffron Walden, UK.  We are seeking a Senior Scientist, a Research Leader and a Group Leader.  More details on the individual posts and on how to apply are in the links below:

Posted 28th July 2019.

Modelling Expert : Syngenta

The Modelling Expert will be a key member of a new group being established to provide early insights to projects inventing new active ingredients (ais), enabling selection and design of compounds with optimised properties to meet society’s needs.

The key area of focus for the Modelling Expert will be to provide QSAR, cheminformatics and mathematical modelling support as part of a cross-functional team. The primary responsibility will be to build predictive models relating chemical structure and/or properties to endpoints relevant for agrochemical research (particularly human safety, human exposure, environmental fate, environmental exposure and ecotoxicology). You will be working within wider project teams aiming to use the models to identify high quality compounds in a streamlined and efficient way, influencing chemical synthesis priorities in search of novel ais.

You will need to have a good knowledge of state of the art approaches to QSAR modelling and their utility with a willingness to learn and adapt to the many varied challenges new ai research faces.

More information can be found here .

Posted 12th July 2019.

Machine Learning Expert : AstraZeneca

We are expanding our Artificial Intelligence and Machine Learning (AI/ML) team focused on drug design and are now ready to recruit a dedicated Machine Learning Expert.

We believe that you are a true Machine Learning authority, ready to contribute to drug development projects right from the start. This role will challenge and encourage you to execute and develop as scientist in a highly creative atmosphere. You will be part of a team that operates in a highly cross disciplinary environment in close collaboration with a broad variety of experts across the company.

You will join a highly collaborative and innovative environment where you can exchange ideas with other experts in the field, and where plans are put into practice. Your Machine Learning knowledge combined with your high ambition and enthusiasm gives you a superb opportunity to influence the development of AstraZeneca’s future in applying ML/AI to drug discovery projects.

Main Responsibilities

  • Extracting and modelling large data sets
  • Applying state-of-the-art machine learning algorithms
  • Passion for machine learning in particular and science in general
  • Interact closely with experimentalists that will validate your predictions
  • Plan, write and publish high quality scientific papers in high-impact machine learning and medicinal chemistry journals
  • Establish academic collaborations to access and drive the forefront of ML for drug development
  • Actively participate in mentoring the cohort of Postdocs, PhD students and Master Thesis students in the team

More information can be found here.

Posted 28th May 2019.

Job opportunity at Oxford Drug Design  

Oxford Drug Design is a unique biotechnology company. Supported by a proprietary set of computational chemistry methods developed in-house over the past 15 years, we are discovering new antibiotics to address the urgent threat of multi-drug resistant infections. Following success in obtaining funding from Innovate UK, the UK’s Innovation agency, we are expanding our computer-aided drug design (CADD) team.

Your Role:

  • • Develop and validate novel CADD methodology in the areas of machine learning, statistical methods, chemgenomics and computational chemistry, working in a multidisciplinary team of internal and external colleagues, and be a key contributor to their success.
  • • Use a diverse array of computational technology to devise hypotheses for structure-activity relationships and compounds to test these hypotheses, focused on our antibiotic drug discovery portfolio.
  • • Maintain and build our internal cheminformatics databases and search technologies.
  • • Maintain awareness of the latest technologies and developments in CADD and project areas.
  • • Maintain an internal and external scientific presence by authoring significant scientific presentations and publications.

More information can be found here.

Posted 1st April 2019.

Chemoinformatics Data Scientist, BenevolentAI

BenevolentAI harnesses artificial intelligence to accelerate scientific discovery by making sense of highly fragmented information to develop new medicines for hard to treat diseases, using AI as a force for good.

Based on a year of strong growth, further validation of the core AI technologies and recent acquisition of laboratory space, we are recruiting a Cheminformatics Data Scientist (Machine Learning) into the Cheminformatics Team to support our Cheminformatics research and development of new methods and tools. We are keen to hear from Cheminformatics Data Scientists, with a proven track record of processing and analysing chemical datasets and endpoint data, particularly developing and applying techniques from Machine Learning.

Challenging and meaningful, this role will give you a chance to bring your own experience, ideas, and creativity to push forward exciting projects quickly with the chance to try genuinely new ways to find medicines.

More information can be found here.

Posted 27th March 2019.

Machine Learning for Chemical Synthesis, Astrazeneca

Do you have expertise in, and passion for, Chemistry and Machine Learning?Would you like to apply your expertise to impact the digital transformation strategy in a company that follows the science and turns ideas into life changing medicines? Then you might be the one we are looking for!

As a Senior Scientist/Associate Principal Scientist within the Computational Pharmaceutics team, you will lead scientific development in one of following areas.

  • Synthesis planning:  Developing synthesis planning approaches for route selection and process design using AI & ML approaches.  This role is focused on reaction optimization and route design to support drug development. The role will exploit internal and external databases to develop route selection workflows optimized for AstraZeneca chemists. The role is placed either in Macclesfield (UK) or in Gothenburg (Sweden).
  • Data scientist for process design:  Working with the Pharmaceutical sciences community to adopt a data-first culture, recognizing opportunities to utilise AI & ML to generate knowledge and innovation and work alongside scientific experts to design projects to optimize underlying data structure. The role will focus on data extraction, analysis and capture strategies to support data-driven decision making. As the lead Data Scientist in ECD you will maintain awareness of state -of-the art applications of AI and engage with AZ leadership to design and influence strategic decisions. The role is placed Gothenburg (Sweden).

Welcome with your application no later than April 14, 2019

Full details can be found here

Posted 13th March2019

Scientific Software Developers, Astex, Cambridge

The role offers a range of opportunities to develop scientific software in the structure-based drug design
(SBDD) and cheminformatics areas, using state-of-the art technologies including the application of artificial
intelligence. The ideal candidate will be a computational chemist or biologist with an aptitude for software
development, or a computer scientist with experience of working in a chemistry and/or structural biology related
discipline. The applicant will have a keen interest in developing web applications.
Principal Responsibilities
• Design and develop bespoke SBDD and cheminformatics web applications
• Keep abreast of the latest technologies to identify new opportunities
• Promote close interactions across multidisciplinary groups
• Collaborate with biologists, structural biologists, chemists and software developers
• Iteratively develop tools and methods on the basis of feedback from in-house users
• Provide informatics support for drug discovery programs
Skills and Experience Required
• Degree in chemistry, biology, computer science or related field
• Proven software development experience working in industry or an equivalent academic setting
• Expert knowledge in Python and at least one other language: Perl, Java, C++, Javascript
• Experience with relational databases e.g. Oracle, MySQL
• Experience with full stack web development
• Familiarity with common software development tools and practices (version control, testing, etc.)
• Excellent team working, written and verbal communication skills
We offer excellent training and career development opportunities as well as a highly competitive salary and
benefits package.
Closing Date: 13th January 2019
To apply, please send your CV and a cover letter quoting the job reference: SDD/1218 to

Computational Chemist, OMass, Oxford

OMass Technologies specializes in applying state-of-the-art native mass spectrometry
platforms to characterizing challenging protein assemblies, including membrane proteins. By
preserving the structures of protein assemblies we provide novel structural insights into
large, dynamic complexes. The company vision is to build a drug discovery company with
these technologies at its core.

We are seeking an experienced Computational Chemist to join the growing research team at
OMass to support the company’s discovery programmes. This is an exciting opportunity to
undertake an extremely dynamic and diverse role within a new biotechnology spin-out
company from the laboratory of Professor Carol Robinson at the University of Oxford. The
company offers a thriving and creative environment for a well-suited candidate to be
exposed to drug discovery and development processes and state-of-the-art technology
developments. You will acquire extensive knowledge of the company’s operations and
become an integral part of our future vision.

At OMass you will join a team of enthusiastic and dynamic scientists with a shared passion
for building a world-leading drug discovery company using an exciting and powerful set of
technologies. Following a recent successful fund-raising exercise, the company is expanding
significantly in different areas and currently in the process of moving to a new building at
the Oxford Science Park. This is an excellent time to join a growing company.

The successful candidate will have worked in a pharmaceutical or biotechnology company,
collaborating with medicinal chemists and pharmacologists to identify and optimize small
molecule chemical drug leads. You will have experience with protein-based and ligand-based
design methods. Experience with drug discovery for GPCR targets is preferable, but
not essential.

For full details see here

Posted 12th September 2018

Computational Molecular Design and Data Science (Leaders & Team Members) :GlaxoSmithKline

An exciting opportunity is available to apply the latest in data modeling techniques to the realm of drug discovery.  The last few decades have seen an unprecedented growth of tools and technology to enable the extraction of relationships within and between complex sets of data.  The successful candidate will leverage the tools of drug discovery informatics with the latest in data mining and modeling methods developed in other disciplines and apply them to the prospective modeling of on- and off-target behavior of drug candidates.  The primary focus of these roles will be to work closely with collaborators from a variety of groups to provide data-driven decisions/suggestions on potential. In addition, the successful applicant will help to develop and optimize computational approaches that leverage external and proprietary data for the automated design and selection of small molecules from limited knowledge of drug targets.  The ability to concisely and accurately communicate complex techniques and the results derived from their application to non-experts is essential.

Responsibilities include:
•  Understanding relevant datasets, both those generated internally and those from the public domain.
•  Applying chem-informatics methods to support drug discovery, optimization, and development in medicinal chemistry project team settings.
•  Applying machine learning algorithms to drug discovery problems and educating colleagues about machine learning approaches.
•  Communicating data analysis and modeling results to the collaborators in the GSK scientific community.
•  Engaging in scientific programming and algorithm optimization to enhance our software infrastructure.

For full details please see here 

Posted Sept 10th 2018

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