Postdoctor in Modeling and Control for Bioproduction
KTH Royal institute of technology, EECS
KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as architecture, industrial management, urban planning, history and philosophy.
The research activities of the Division of Decision and Control Systems are focused on system identification, control, machine learning and optimization of dynamical systems, with applications in autonomous systems, networked system, process control, modeling and control of bioprocesses, robotics and secure systems. The personel has a multicultural background and the working language is English. The division is internationally well established and is involved in many European and national research centers and projects. Industrial partners include ABB Corporate Research, ABB Process Automation, BillerudKorsnäs, Ericsson Research, and Scania. We have a large academic network and collaborate with researchers at MIT, UC Berkeley, Stanford University, TU Eindhoven, and Université de Lyon among others. Automation and Control at KTH was ranked 15 in the world in the latest ARWU Shanghai ranking.
KTH offers an attractive working environment and generous remuneration. As a postdoctoral researcher at KTH you have many opportunities to participate at conferences, projects and other relevant events which will extend your professional network and benefit your future career.
Biopharmaceutical industry is a large and profitable field. The field has evolved from production based on bacterial systems towards production based on mammalian cells in a majority of biological drugs. The legacy is fed-batch processing but the field is rapidly evolving as a result of the new trends and a constantly increasing competition. In this perspective, integrated continuous bioprocessing, i.e. a process consisting of a perfusion culture where medium is steadily added, has received very high attention both from industry and academia. This interest is rapidly increasing and nearly all the large Pharma/Biotech companies are looking into this type of intensified process.
Production under such conditions requires feedback control, which in turn requires adequate models for the dynamics of the process. Through several projects we intend to create a sustainable world class environment for modeling and control of bioproduction. Currently the team involves two full Professors with specializations towards data driven modeling and control, two postdocs and one PhD student.
The open postdoc position is associated with the new Centre for Advanced BioProduction, AdBIOPRO, led by KTH, and in collaboration with Lund University and Karolinska University Hospital as well as seven Swedish companies in the Biopharmaceutical/Biotech industry, including GE Healthcare. The Centre focuses on bioproduction based on mammalian cells, with the objective to respond to the paradigm shift towards continuous processing, and with the intention of becoming world leading.
The postdoc project concerns model based optimization and control of culture media and processes. It involves developing methodolgies for mechanistic macroscopic metabolic modeling, parameter estimation and experiment design for such models, optimizing cell metabolism through media feeds for perfusion, and feedback control of perfusion processes. The project is in close collaboration with the School of Biotechnology at KTH, world leading in perfusion and hosting extensive laboratory facilities, and our industrial partners, with the ultimate objective to verify methodologies in an industrial setting. There will also be a close collaboration with the VINNOVA sponsored project “Smart feed design for biopharmaceutical production” (SmartFD), where we collaborate with the School of Biotechnology at KTH, world leading in perfusion, and GE Healthcare and Cobra Biologics as industrial partners.
The postdoc project concerns model based optimization and control of culture media and processes. It involves developing methodologies for mechanistic macroscopic metabolic modeling, parameter estimation and experiment design for such models, optimizing cell metabolism through media feeds for perfusion, and feedback control of perfusion processes. The project is in close collaboration with the School of Chemistry, Biotechnology and Health at KTH, world leading in perfusion and hosting extensive laboratory facilities, and our industrial partners, with the ultimate objective to verify methodologies in an industrial setting.
In summary, the project has a an ambitious scope, spanning model development for bioprocesses, algorithm development for data driven modeling, optimization, and control design, and where industrial relevance will be ensured through the use of laboratory and industrial data and verification. An interesting challenge is to integrate methods from data analytics and machine learning in this context.
We seek candidates with a background from modeling of reaction networks, (parameter) estimation and off- and on-line optimization (such as Model Predictive Control), preferably with applications in bioproduction.
Candidates should have a Ph.D. or be near Ph.D. defense in Electrical Engineering, Chemical Engineering or Biotechnology. The candidate should have a strong background from at least one of the areas bioprocess modeling, system identification or Model Predictive Control, and experience from at least one more of these areas.
The successful applicant should have an outstanding research and publication record. Well-developed analytical and problem solving skills are a requirement. We are looking for a strongly motivated person, who is able to work both independently and in collaboration with others. Good command of English orally and in writing is required to present and publish research results.
Great emphasis will be placed on personal competence and suitability.
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The application should include:
- Full curriculum vitae including your relevant academic, professional, and other achievements, experience and knowledge
- Copy of the degree certificate(s) from your previously attended university-level institutions, with certified translations in English (unless provided so by the issuing institution)
- Statement of purpose: What are your academic interests, how does the project relate to your previous studies and future goals; maximum 2 pages long
- List of publications and copies of two representative publications or technical reports no longer than 10 pages each. For longer documents (e.g. theses), please provide a summary (abstract) and a web link to the full text
- Letters of recommendation
- Contact information for two reference persons
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|Type of employment||Temporary position longer than 6 months|
|Contract type||Full time|
|First day of employment||As agreement|
|Number of positions||1|
|Working hours||100 %|
|Last application date||23.Sep.2019 11:59 PM CET|