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Position: Machine Learning and Cheminformatics Experts

Location: Gothenburg, Sweden

As one of the world's leading pharmaceutical companies, our business is focused on providing innovative, effective medicines that make a real difference in important areas of healthcare. At AstraZeneca, innovation is about more than just research. We're focused on providing medicines that make a real difference in patient care. AstraZeneca is a place where you can drive innovation in small molecule and biological research and development, it's also a place with a collaborative culture, and flexible working environment, where you'll feel valued, energised and rewarded for your ideas and contributions.

Artificial Intelligence and Machine learning has the potential for profound impact in Drug Discovery. We are looking to build our cheminformatics and machine learning team to apply these technologies globally across AstraZeneca Chemistry.

As a key part of this initiative you will combine computational chemistry, cheminformatics and machine learning to progress the AstraZeneca project portfolio. You will work with cutting edge technology in an open and collaborative environment nurturing novel ideas and working alongside drug project teams. Our team is spread across our main 'hub' locations in Cambridge, UK, Gothenburg, Sweden and Boston, USA.

Main Roles and Responsibilities:

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.

You will:

* Impact multiple discovery projects simultaneously by efficiently and pro-actively applying a wide variety of machine learning methods and building models for molecular de novo design, synthesis prediction, ADME and bioactivity predictions.
* Actively contribute to AstraZeneca data integration, machine learning model building and data exploitation efforts.
* Drive scientific leadership in applying machine learning in drug discovery
* Drive scientific progress in machine learning through supervising postdocs, PhD students.
* Plan, write and publish high quality scientific papers

Essential Requirements

* We are seeking candidates who share our passion for Drug Discovery with a PhD (or equivalent experience) in Computational Chemistry, Cheminformatics or Computer Science, and preferable industry experience who would like to join our fast-paced multidisciplinary Discovery Sciences computational chemistry team.

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

If you are interested, please apply now, uploading your CV and covering letter.

AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, sex or sexual orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law.

Detta är en jobbannons med titeln "Machine Learning and Cheminformatics Experts" hos företaget AstraZeneca och publicerades på webbjobb.io den 6 augusti 2018 klockan 14:20.

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