Research Fellow in the Determination of Particle / Bulk Powder Physical Property Attributes for Pro
- Employer
- Global Academy Jobs
- Location
- United Kingdom
- Closing date
- Jul 5, 2018
View more
- Sector
- Science, Physical Sciences and Engineering, Chemical Engineering, Chemistry, Biochemistry
- Hours
- Full Time
- Organization Type
- University and College
- Jobseeker Type
- Academic (e.g. 'Lecturer')
Job Details
Do you have a background in the characterisation of the physical properties attributes of single particles and/or bulk powder, and pharmaceutical production processes?
Do you have a passion to uncover the links between the measured properties of active pharmaceutical ingredients, excipients and blends and drug product (compact) attributes and manufacturing behaviour, through established science of scale and computational approaches?
Do you want to further your career in one of the UK’s leading research intensive Universities or pharmaceutical industries?
You will be a member of the team of the £20.4M Advanced Digital Design of Pharmaceutical Therapeutics (ADDoPT) project, which has been funded by the Department for Business, Energy and Industrial Strategy’s Advanced Manufacturing Supply Chain Initiative. The project is industry-led and is being delivered by a consortium of companies and academic institutions. The aim of the ADDoPT project is to accelerate the translation of molecules into medicinal products. Your position is directed towards the generation and curation of physical properties data relating to pharmaceutical drug product processing. The post will be based at Pfizer’s research facility in Sandwich, Kent, UK. Pfizer is one of the pharmaceutical prime companies within the ADDoPT project. This research work is led by Pfizer, Bristol-Myers Squibb, AstraZeneca and GlaxoSmithKline in collaboration with the University of Leeds and the Science and Technology Facilities Council’s (SFTC) Hartree “Big Data” Centre. This is an exciting opportunity to undertake internationally-leading research in the development of process/statistical models through the generation of high-quality datasets.
To explore the post further or for any queries you may have, please contact:
Prof. Kevin Roberts, School of Chemical and Process Engineering Tel: +44 (0) 113 343 2408 or email k.j.roberts@leeds.ac.uk
Dr. CaiYun Ma, School of Chemical and Process Engineering Tel: +44 (0) 113 343 7809 or email c.y.ma@leeds.ac.uk
Company
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