Postdoc in AI and Machine Learning in Food Processing Technology
Modern food science and food processing generates enormous amounts of continuously incoming data that needs to be analyzed quickly and reliably, and current methods for data analysis are challenged to the limit. For this reason, DIKU (Department of Computer Science), FOOD (Department of Food Science) at the University of Copenhagen and FOSS Analytical have decided to join forces and invest in new groundbreaking research based on machine learning methods with the purpose to extract and explore relevant information from continuously developing big data sets.
The focus of the research will be on data processing of on-line quality monitoring of various manufacturing systems with emphasis on data procured from food manufacturing process. The project will also investigate processing of large and parallel multivariate sequential data streams and metabolomics/foodomics data analysis. As a candidate, you are not required to have experience in all of these fields, but you should be able to generalize your knowledge onto the research themes that are new to you. Candidates with prior knowledge of food manufacturing processes and/or metabolomics will be preferred.
We seek an entrepreneurial postdoc who has obtained a PhD degree in data analysis from a computer science department (or similar), and who has a genuine interest in developing new methods for deep data processing, including exploration and regression of complex food related systems. The candidate must have an academic experience including topics such as:
- Artificial intelligence
- Machine/deep learning
- Time series analysis
- Data streaming and storage
The candidate must be ready for the challenges of creating information from gigantic data sets. The position is sponsored as a collaboration between DIKU, FOOD, and FOSS Analytical A/S. FOSS Analytical A/S is developing advanced analytical instruments for laboratory and process analytics in the food and agricultural industry.
The postdoc’s duties will include research within big data and machine learning in food science and food processing technology as described above, as well as participate in teaching the department courses. The post may also include performance of other duties in the research groups. The postdoc will be hosted by FOOD, but it is required that the postdoc will share her/his working place amongst the three stakeholders as appropriate for solving the challenges.
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 Professor Søren Balling Engelsen (firstname.lastname@example.org).
The position is open from 1 October 2022 or as soon as possible thereafter and will have a duration of 22 months.
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 14 August 2022, 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/.
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.