stillingsbetegnelse:
PhD scholarship in Validation and Improvement of Property and Process Modelling for Oleochemicals

jobbeskrivelse:
The PhD position will be supervised at the CAPEC-PROCESS research center of DTU Chemical Engineering department in joint cooperation with Alfa Laval Copenhagen which provides the employment for this position. It is an early stage researcher (ESR) position and part of ?ModLife: Advancing Modelling for Process-Product Innovation, Optimization, Monitoring and Control in Life Science Industries? ? a H2020-MSCA-ITN-2015 project funded by EU Executive Research Agency (ERA). More information about the project can be accessed at modlife.eu. Responsibilities and tasks • Supervisors: Dr. Bent Sarup (Alfa Laval), Assoc. Jens Abildskov (DTU), Prof. Gürkan Sin (DTU) • Objectives: (1) Improving accuracy of property and process models for describing mixtures relevant for oleochemical industries in particular fat-oil splitting. (2) To identify validation strategies and methods for improving property and process modelling. (3) To generate and collect data for validation and improving property/thermodynamics models relevant for oleochemicals. In particular to develop kinetic and thermodynamic models for describing fat-oil splitting process. Moreover, the project includes data collection about mixtures (VLE, LLE, etc) in joint collaboration with specialized labs. Use of full scale data from oleochemicals production is also another possibility. Validated models are used to simulate, design and optimization and control strategies on selected oleochemical processes including recovery of high value added products. • Expected results: (1) Systematic identification/review of the gaps in the property models, the needs for data for further improvement and validation, (2) Generation/Collection of new pure component as well as mixture data relevant for oleochemicals, (3) Improved property models for predicting phase equilibrium of mixtures relevant to oleochemicals (lipids, derivatives of fatty acids, etc), (4) Comprehensive uncertainty analysis of prediction accuracy of improved models, (5) Validation of the models demonstrated for selected oleochemical processes in collaboration with ESR10 including fat-oil splitting and fatty acids distillation. Validated models are used to formulate advanced optimization and control strategies in ESR10. • Planned secondments: DTU, 3 months: property modelling and uncertainty analysis. Qualifications Candidates should have a master's degree in engineering or a similar degree with an academic level equivalent to the master's degree in engineering. Approval and Enrolment The scholarships for the PhD degree are subject to academic approval, and the candidates will be enrolled in one of the general degree programmes of DTU. For information about the general requirements for enrolment and the general planning of the scholarship studies, please see the DTU PhD Guide. Assessment The assessment of the applicants will be made by Assoc. Prof. Gürkan Sin, Dr. Bent Sarup and Dr. Alexandr Zubov. The following competences are desirable in the candidates: • Experimental/measurement competences. In particular, generation/collection of new pure component as well as mixture data relevant for oleochemicals (VLE, LLE, etc). • Model validation/improvement for property and process models in particular for oleochemical processes. • Process/property modelling and parameter estimation. • Being an industrial Ph.D. position some years of industrial background will be an advantage. Since the positions is ESR position funded by H2020-MSCA-ITN-2015, the following eligibility and mobility criteria holds: • The candidate must be ? at the date of recruitment ? an ?early stage researcher? (i.e. in the first four years of his/her research career and not have a doctoral degree). • At the time of recruitment by the host organisation, researchers must not have resided or carried out their main activity (work, studies, etc) in the country of their host organisation for more than 12 months in the 3 years immediately prior to the

Timer per uge: Tills vidare

Arbejdsgiver Navn: Danmarks Tekniske Universitet

Form af kontakt: Maj Hansen

Job kort beskrivelse:
Undervisning og forskning på universiteter og højere læreranstalter

land: Danmark

region: Hovedstaden

Kontrakt varighed: Fast

Kontrakttype: Fuldtid

krævede uddannelse: Ikke angivet

Kilde til jobtilbud: AMS, Offentlige arbejdsformidlinger, Danmark