Postdoc in “Minimising the Environmental impact of Cleaning”
There is an increasing demand for sustainable processing for example in terms of reducing of energy and water demand. Cleaning In Place (CIP) processes have a significant environmental bearing, in terms of energy consumption (estimated at 20% of the total energy used in manufacturing), water usage and use of chemicals. There is a substantial risk in product quality and safety associated with reducing the intensity of CIP processes making optimization challenging. Monitoring tools and advanced data analytics at industrial scale provide an opportunity that can be augmented by using models that capture the relevant physico-chemical phenomena.
The position is open from 01 June 2023 or as soon as possible thereafter. The duration of the position is for 2½ years.
The aim of the Position is to develop models that will enable optimization of Cleaning in Place (CIP) processes in the dairy industry. The research will use existing knowledge to develop physics based models to capture fundamental mechanisms at microscopic and macroscopic scales during cleaning. Models will be formulated to capture the uncertain and probabilistic nature of the phenomena. The research will benefit from models developed through an ongoing PhD programme.
Who are we looking for?
We are looking for highly motivated candidates with an interest in process modelling.
- a PhD (or soon-to-be PhD) in the areas of process modelling , PAT
- Academic preparation as well as (proven) experience in statistical analysis
- Strong programming skills in Python or Matlab
- Proven track record showing scientific productivity in peer reviewed journals (in relation to applicants’ career trajectory)
- Demonstrated capacity for effective teamwork
- Experience in supervising other researchers at different levels
- Excellent English communication skills, both written and oral
The following qualifications are highly preferred, but not required. Candidates who possess any of these qualifications are encouraged to highlight them in the application:
- Previous postdoc experience
- Experience in the areas of Markov-Chain; Monte Carlo and/or Approximate Bayesian Computation
- Experience in developing physics based machine models for process engineering problems
- Experience in Process Analytical Technology
- Previous experience in public outreach
The postdoc’s duties will include research within food science as well as teaching. The post may also include performance of other duties.
Further information on the Department is linked at https://www.science.ku.dk/english/about-the-faculty/organisation/. Inquiries about the position can be made to Prof. Serafim Bakalis (email@example.com)
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.
Terms of appointment and payment accord to the agreement between the Danish Ministry of Taxation and The Danish Confederation of Professional Associations on Academics in the State.
Negotiation for salary supplement is possible.
The application, in English, must be submitted electronically by clicking APPLY NOW below.
- Curriculum vitae
- Diplomas (Master and PhD degree or equivalent)
- Research plan – description of current and future research plans
- Complete publication list
- Separate reprints of 3 particularly relevant papers
The deadline for applications is 15 April 2023, 23:59 GMT+2
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee.
You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.
Interviews will be held on the 4th and 5th of May 2023.
Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.