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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, Syngenta, Berkshire

We are looking for a highly motivated computational chemist to join the Structural Biology and Computational Chemistry group at our R&D site in Jealott’s Hill, UK. The role offers an exciting opportunity to work on chemistry design problems in a multidisciplinary environment, with applications in a wide range of biological systems spanning plant, mammalian and invertebrate biology.

The successful candidate will need to demonstrate flexible teamwork and a tenacious approach to delivering computational chemistry outputs to research projects. Excellent oral and written communication skills and the ability to translate specialist knowledge into a meaningful output for multidisciplinary project teams are highly desirable qualities for this position.

Full Details Here

Posted 19th October 2018

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

Application Scientist – Chemical Computing Group

Chemical Computing Group (CCG) is a life science software company producing leading drug discovery technology for pharmaceutical and biotechnology companies. Reporting to a Director of Scientific Support, this position requires computational drug discovery experience as well as superior interpersonal skills. We currently have an open position in Cambridge, UK.

In this role, you will be expected to:

  1. Effectively interpret customers’ scientific problems and queries and resolve them as required by phone, email or meetings.
  2. Provide on-site customer support including formal presentations, demonstrations, training and discussions with a view to increasing usage of MOE applications.
  3. Create customized software solutions using our in-house SVL scripting language.
  4. Produce course materials, tutorials and other technical documents for pedagogical purposes.
  5. Perform original research to produce scientific talks and posters and present them at conferences, workshops and customer visits.
  6. Collaborate with CCG’s research and development team for software testing and discussions on software development.
  7. Provide recommendations to CCG sales and management teams to ensure that customers’ expectations are met.
  8. Be a well-respected and trustworthy resource for our clients.

Full details can be found at this link

Posted June 21st 2018

Machine Learning and Cheminformatics Experts : Astra Zeneca

You will have a profound impact on multiple projects across AstraZeneca Discovery with a focus on building machine learning models and applying the models together with the project team to discover new drugs. You will have a key role in creating datasets for machine learning, molecular de novo design, synthesis prediction drug design, and models to predict target activities. A major component will be to assure that AstraZeneca gets a maximum value out of all of its proprietary data. You will also provide discipline based scientific leadership and represent the department and AstraZeneca at interdisciplinary meetings internally as well as externally.

Key qualities:

  • Expertise in a variety of machine learning methods (e.g. Deep Learning, SVM, Random Forrest)
  • Solid knowledge of computational chemistry; Cheminformatics and Machine Learning concepts
  • Proven expertise in high-performance computing and programming (e.g. Python, C++, Java)
  • Expertise in applying machine learning models into projects
  • Very good written and verbal communication skills
  • Excellent publication track record

Full details can be found at this link

Posted May 1st 2018

Post Doc Fellow – Predictive chemistry tools for route design, Macclesfield, UK: Astra Zeneca

Predictive modelling is a developing area in route design requiring the calculation and comparison of transition states to predict chemo/regio-selectivity and reactivity for reactions.  Currently predictive reaction modelling is time consuming, utilizing numerous computationally expensive approaches, with varied prediction accuracy across different reaction classes. We are looking for a chemist with a computational background that has a good understanding and strong experience in reactivity modelling.

  • The candidate will be responsible for the development and application of predictive reactivity models for key reaction classes.
  • The candidate will employ quantum theoretical reaction path modelling, quantitative structure-reactivity relationships (QSRR) using physically meaningful mechanistic molecular descriptors and hybrid models that combine both approaches with experimental data.
  • The candidate will critically assess and select optimal predictive models for application in route design activities.
  • Working with project chemists the candidate will explore the applicability of the novel predictive models though testing and validation on novel systems as part of drug development projects.

The candidate will have the opportunity to present both internally and externally on project achievements and publish the results in high impact journals.

This is a 3 year programme.  2 years will be a Fixed Term Contract, with a 1 year extension which will be merit based.  The role will be based at Macclesfield, UK, with a competitive salary on offer.

Advert closing date – 13th May 2018

Full details can be found at this link

Postdoctoral Research in Computational Chemistry, Syngenta, Jealott’s Hill, UK

We have an exciting vacancy for a postdoctoral researcher in Computational Chemistry. In this role, you will provide cheminformatics and mathematical modeling support as part of a cross-functional team. The primary role of this position is to build and use models to predict endpoints relevant to agrochemical research based on chemical structure, descriptors and/or properties.  You will be working within a wider project aiming to use models to identify high quality compounds in a streamlined and efficient way, influencing chemical synthesis priorities in search of novel active ingredients.

The Job entails:

  • Building predictive models relating chemical structure and/or properties to endpoints relevant for agrochemical research (such as environmental safety, human safety and biological efficacy)
  • Liaison with functional representatives to understand data and modelling requirements
  • Interrogation and curation of data for model building
  • Developing and deploying predictive models to end users
  • Communicating and documenting model development

Critical Experience and Skills:

  • A PhD or equivalent in cheminformatics or a related field
  • Understanding of chemical structure and properties
  • Knowledge of applied statistical methods for data analysis (univariate and multivariate methods)
  • Experience in predictive modelling (such as multiple linear regression, machine learning e.g., SVM, random forest)
  • Experience with R and/or python essential (experience with work flow tools such as KNIME, pipeline pilot desirable)
  • Knowledge relating to kinetic modelling (in either environmental or mammalian systems) would be advantageous. If not, willingness to learn is a requirement.
  • Ability to communicate across functional boundaries

This position will be for a period of 12 months with the possibility to extend.

How to apply     

Please email a CV, research summary and covering letter to: quoting the job reference [PDCC2] in the subject line. Deadline for applications: Thursday 29th March 2018.

Associate Principal Scientists, AstraZeneca 

AstraZeneca is now recruiting two Associate Principal Scientists with speciality in Computational Pharmaceutics to join the Early Product Development (EPD) function within Pharmaceutical Sciences at AstraZeneca. One role focuses on Biopharmaceuticals and is placed in Gothenburg (Sweden). The other role focuses on Solid state and material properties and could be placed either in Gothenburg (Sweden), Macclesfield (UK) or Cambridge (UK).

As an associate principal scientist in Computational Pharmaceutics, you will be part of EPD to lead scientific development in one of following modelling areas.

  • Biopharmaceutical: Modelling of distribution, dissolution and absorption of drug compounds and formulated products. This role is focused on modelling of inhaled emergent products for new modalities. The role is placed in Gothenburg, Sweden.
  • Solid state and material properties: Prediction of crystal structures, exploring polymorph landscape, prediction of morphology, crystal growth and crystallization conditions, prediction of mechanical properties and surface-surface/surface-particle interactions and aiding selection of co-formers through modelling. The role is placed either in Gothenburg (Sweden), Cambridge (UK) or Macclesfield (UK).

Full details can be found at this link.

Posted March 2018

Exscientia (various positions)

Exscientia is at the forefront of Artificial Intelligence (AI) driven drug discovery.  Our AI driven systems actively learn best practice from vast repositories of drug discovery data and are further enhanced with knowledge acquired from seasoned drug hunters. Our team are passionate in the pursuit of excellence and at Exscientia you will enjoy a flexible, inspiring and dynamic working environment. Exscientia is an equal opportunity employer committed to building a culturally diverse team.

Full details can be found at this link.

Posted February 2018

Structure-Based Drug Design (SBDD) Science Expert: CCDC, Cambridge/UK

The CCDC is looking for full-time SBDD Science Expert to join their team.

CCDC has a role for a talented individual to product manage CCDC’s life sciences portfolio in drug discovery. The ideal candidate would act as an evangelist for CCDC software and services to the customer base, would manage and maintain the product life cycle of key CCDC products and would help to guide research & development towards critical areas where CCDC software & services can have impact.

The successful candidate will work extensively with the Head of CCDC’s Life Sciences R&D team and team members to facilitate setting of the strategic direction for life sciences, ensuring strong alignment with key customer needs.

Applicants should send a CV and a covering letter to Kirsty Day, HR Officer, CCDC, 12 Union Road, Cambridge CB2 1EZ, or via email to Here are job description and candidate profile.

For an informal chat about the position please contact 01223 336408.

Full details can be found at this link.

Posted September 2017

Sales Manager, Europe: CCDC, Cambridge/UK

The CCDC is looking for a full-time European Sales Manager.

The post holder will develop business relationships between the CCDC and its user communities in Europe and Asia.  This will include creating sales plans, overseeing annual renewals processes, developing positive business relationships (with existing users as well as creating new industrial engagements across Europe).  The individual will seek out new sales channels into new territories, represent CCDC positively at varying events and oversee the work and processes of the internal sales and operations team.

Applicants should send a CV and a covering letter to Kirsty Day, HR Officer, CCDC, 12 Union Road, Cambridge CB2 1EZ, or via email to Here are job description and candidate profile.

For an informal chat about the position please contact 01223 336408.

Full details can be found at this link.

Posted September 2017

Quantitative Systems Toxicologist: GSK, Harlow/UK

As a post-doctoral appointment in Quantitative Systems Toxicology (QST). The successful candidate will be passionate about using advanced mathematical modeling and computational sciences to support drug discovery and development. Working in a dynamic, multidisciplinary environment, you will develop and deploy systems biology based models encompassing knowledge of chemistry, computational biology, pharmacology and importantly, toxicology, to integrate mechanistic safety and drug disposition data to support drug discovery and development, facilitate the identification and progression of new molecular entities, and reduce attrition.

The position is an exciting opportunity to support translational safety assessment by leveraging GSK legacy toxicity and disposition data to support multi-scale modelling that supports mechanistic understanding and human risk assessment.

The successful candidate will work collaboratively in matrix teams to prioritize model generation, based on testable hypotheses to predict toxicology. You will ensure that work is aligned with strategic priorities, and seek out new opportunities for impact of quantitative systems toxicology methodologies on drug discovery at GSK. In order to be effective, you will need to build close relationships and influence a wide variety of business partners, think flexibly and collaboratively, and exemplify the GSK behaviours and expectations.

This is an opportunity for a highly motivated individual to have an impact in a exciting and rapidly growing field of computer aided drug design, informatics and mechanistic safety sciences rooted in the belief that theoretical models based on exploitation of data and knowledge of chemical reactivity and biological processes can drive the development of safe drugs more efficiently and robustly.

GlaxoSmithKline is a world leading research-based pharmaceutical company that combines both individual talent and technical resources to create a platform for the delivery of strong growth in a rapidly changing healthcare market. Our mission is to improve the quality of human life by enabling people to do more, feel better and live longer.

Full details can be found at this link.

Posted 21st August 2017.

Computational chemist: Cresset, Cambridge, UK

Computational chemist with programing/scripting experience required to assist with development of new scientific techniques, and turn these into industry-leading easy-to-use software products.


  • Assist in researching, specifying, designing and helping to implement the next set of cutting-edge software tools
  • Manage and contribute to scientific research projects
  • Produce scientific papers
  • Present research worldwide to Cresset customers and at scientific conferences

More details available here.

Postdoctoral Researcher in Computational Drug Design:  Pedro Ballester Lab, INSERM, Marseille/France

Working environment

The Cancer Research Center of Marseille (CRCM) is the basic science and translational research unit of the private cancer hospital Institut Paoli Calmettes (IPC). Also affiliated to INSERM , CNRS and Aix-Marseille University, the 250 researchers working at the CRCM form a strongly multi-disciplinary research environment characterized by close collaborations with IPC clinicians. IPC and CRCM form part
of the comprehensive cancer centre Marseille SIRIC (  Further information available at


This project aims at investigating machine-learning models able to identify drug-like molecules with previously unknown activity on a given cancer cell line. The most promising predictions will be experimentally validated by internal and external collaborators. The targets of the resulting phenotypic hits will be identified using existing molecular target prediction tools, including some developed in-house, to make an initial assessment of their efficacy and possible side-effects. A similar approach will be followed to identify synergetic drug combinations on a given cancer cell line. This project was fundedby the competitive ANR Tremplin-ERC programme:








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