Jobs

To support the QSAR and Chemoinformatics community, we post relevant jobs on this web page. If you would like to advertise please contact us by email (ukqsar@ukqsar.org).

 

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: sarah.whalley@syngenta.com 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 careers@ccdc.cam.ac.uk. 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 careers@ccdc.cam.ac.uk. 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.

Responsibilities:

  • 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 (http://www.siric-marseille.fr/LesSIRICS.html?lang=en).  Further information available at http://crcm.marseille.inserm.fr/fileadmin/Recherche/CRCM_Plaquette.pdf

Project

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: http://www.agence-nationale-recherche.fr/en/projects-and-results/archive-of-calls-for-proposals/aap-en/tremplin-erc-t-erc-second-call-2017/

 

 

 

 

 

 

 

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