|CCL 19.08.15 Machine Learning/AI Data Scientist|
From: jobs at ccl.net (do not send your application there!!!)
To: jobs at ccl.net
Date: Thu Aug 15 08:53:33 2019
Subject: 19.08.15 Machine Learning/AI Data Scientist
Machine Learning/AI Data Scientis The Drug Discovery Unit (DDU) (see http://www.drugdiscovery.dundee.ac.uk) is a fully integrated drug discovery operation based within a world class Life Sciences research environment. The DDU houses about 100 scientists structured in discipline focused teams (Medicinal Chemistry, Structural Biology, Computational Chemistry, Biophysical Screening, Biology, Compound Management, ADME/PK). Its remit is to complement BioPharma activities by tackling both neglected diseases (apicomplexan, tuberculosis and kinetoplastid disease) and validation of novel targets and mechanisms across a range of potential therapeutic areas. The DDU works to Biotech style philosophy and standards incorporating, dynamic, goal driven project management based on Target Product Profiles and Compound Selection Criteria. The project goals are therapeutic area dependent but range from quality leads demonstrating disease model proof of concept, through to pre-clinical candidates. Artificial Inteligence (AI) and Machine/Deep Learning (ML) are revolutionising the drug discovery process and the way compounds are optimised to achieve the desired biological activity and pharmacological profile. The DDU Computational Chemistry Team is looking for a highly motivated Data Scientist to develop and establish our AI/ML capabilities. The successful candidate will work as part of our multi-disciplinary drug discovery teams and will play a critical role in the development and implementation of AI/ML methods to drive compounds biological activity and pharmacological profile optimisation. The post is open ended and available immediately. Starting salary from 32,236 to 39,609 depending on experience. A relocation allowance is available. Necessary skills and experience: - Highly motivated, self-directed individuals professionally qualified with EITHER: a PhD in computational chemistry, bio/cheminformatics, or a related topic; OR with a BSc degree in computational chemistry, bio/cheminformatics, or a related topic and substantial subsequent experience in machine learning/ artificial intelligence - Experience in the application of AI/ML methods in modelling complex data - Advance programming in Python - Strong scientific background with an understanding of the Drug Discovery process - Ability to work independently, and in close collaboration with discovery scientists as part of a team - Good time management, organizational and communication skills. - Strong interpersonal, communication and presentation skills Desirable Experience: - Working knowledge of statistics - Expertise in Multiparameter optimisation - Exposure to drug discovery projects A few facts about The College of Life Sciences at Dundee: The School of Life Sciences has over 900 research and support staff from 59 countries and external funding in excess of 40 million per year Dundee has twice been named the best place to work in Europe in a poll of scientists conducted by The Scientist magazine The School of Life Sciences has been consistently rated 5-star (the highest rating) by the UK national Research Assessment Exercise. Dundee, set on the east coast of Scotland, lies in an area of outstanding natural beauty, including large sandy beaches and challenging hills. The diversity of our staff and students helps to make the University of Dundee a UK university of choice for undergraduate, postgraduate and distance learning. Family friendly policies, staff networks for BME, Disabled and LGBT staff, membership of Athena SWAN, the ECU Race Equality Charter and Stonewall as well a full range of disability services, create an enjoyable and inclusive place to work.
https://www.jobs.dundee.ac.uk/fe/tpl_uod01.asp?s=4A515F4E5A565B1A&jobid=103540,0215234821&key=142399549&c=87485965715756&pagestamp=sebiuuhirrhrhjzlhsNOTE THAT E-MAIL ADDRESSES HAVE BEEN MODIFIED!!!
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|Modified: Thu Aug 15 12:53:33 2019 GMT|
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