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Position: Research Fellow in optimization and control of continuous pharmaceutical manufacturing
Institution: University College London
Department: Chemical Engineering
Location: London, United Kingdom
Duties: To develop and implement novel methods integrated design and operability in pharmaceutical process flowsheets. Employ machine learning approaches for quantifying and incorporating uncertainty considerations in optimisation problems and surrogate-based optimisation. To plan and execute real options analysis of different design configurations to account for and manage risk under different market scenarios
Requirements: The successful candidate must a PhD in Engineering, Operations Research or Computer Science. The applicant must either have already completed a doctorate, or have submitted their thesis prior to taking up the post. Proven publications track record in developing novel techniques for dynamic optimization and/or data-driven optimization and/or pharmaceutical manufacturing modelling. Experience in machine learning for uncertainty quantification and modelling. Experience of working in a multi-disciplinary research environment so as to conduct effectively collaborative research
   
Text: Research Fellow in optimization and control of continuous pharmaceutical manufacturing, - Ref:1879884 Click here to go back to search results Apply Now UCL Department / Division Chemical Engineering Location of position London Grade 7 Hours Full Time Salary (inclusive of London allowance) £36,770 - £39,843 per annum Duties and Responsibilities This position is in the Product and Process Systems Engineering Group. The investigators are members of the Centre for Process Systems Engineering (CPSE), a joint centre between Imperial College London and University College London. The project is funded by the Engineering and Physical Sciences Research Council (EPSRC) and is in collaboration with investigators from University of Sheffield (UK), University of Strathclyde (UK) and Purdue University (US). The project aims at developing next generation process optimization and control methods for agile continuous pharmaceutical manufacturing (CPM). To develop and implement novel methods integrated design and operability in pharmaceutical process flowsheets. Employ machine learning approaches for quantifying and incorporating uncertainty considerations in optimisation problems and surrogate-based optimisation. To plan and execute real options analysis of different design configurations to account for and manage risk under different market scenarios. Duration is 34 months in first instance. Key Requirements The successful candidate must a PhD in Engineering, Operations Research or Computer Science. The applicant must either have already completed a doctorate, or have submitted their thesis prior to taking up the post. Proven publications track record in developing novel techniques for dynamic optimization and/or data-driven optimization and/or pharmaceutical manufacturing modelling. Experience in machine learning for uncertainty quantification and modelling. Experience of working in a multi-disciplinary research environment so as to conduct effectively collaborative research. Experience or willingness to work with gPROMS modelling suite. Proficiency with optimisation packages (e.g. GAMS, Pyomo). Experience in programming languages (e.g. Python, Julia) and maintaining online repositories (e.g. GitLab/GitHub). Candidates must have excellent communication and team-working skills, the ability to write high-standard reports and work collaboratively with colleagues to generate high-quality research outputs. Further Details A job description and person specification can be accessed at the bottom of this page. To apply for the vacancy please click on the Apply Now button below. If you have any queries regarding the vacancy or the application process, please contact Dr. Vasileios Charitopoulos at v.charitopoulos@ucl.ac.uk or Prof. David Bogle at d.bogle@ucl.ac.uk. UCL Taking Action for Equality Closing Date 20 Aug 2022 Latest time for the submission of applications 23:59 Interview date TBC Our department holds an Athena SWAN Silver award, in recognition of our commitment and demonstrable impact in advancing gender equality. This appointment is subject to UCL Terms and Conditions of Service for Research and Support Staff. Please use these links to find out more about UCL working life including the benefits we offer and UCL Terms and Conditions related to this job. Job description and Person specification Apply Now
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