Postdoc of Machine Learning applied to Plant Physiology
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The University of Copenhagen is seeking a Post Doc in Data Science. The position is for 32 months, and the successful candidate will be part of the Data Science Lab (DSL, datalab.science.ku.dk) and the Crop section at PLEN. You will work in close collaboration with Associate Professor Erik Dam ([email protected]) and Professor Kristian Thorup-Kristensen ([email protected]).
The job
Being employed at the Department of Computer Science (DIKU), you will be part of our interdisciplinary team of researchers from DIKU and the Department of Plant and Environmental Sciences. At DIKU, you will be part of and collaborate with colleagues in the Machine Learning section and the SCIENCE AI Centre. DIKU is ranked 25 on the 2019 Shanghai world ranking for computer science / engineering departments.
The researcher will develop machine learning methods for analysis of multi-modal time series data. The project will focus on data from the RadiMax facility at PLEN including sub-soil root images, drone field images, genetic data, environment observations, and interventional parameters.
The overall research goal is to use deep learning approaches to exploit data from root phenotyping in the RadiMax facility for improved plant breeding towards plant genotypes with deep and efficient root growth. In the studies in the facilities, hundreds of genotypes of wheat, grasses and potatoes are phenotyped for deep root growth and other traits, and 1000 root images per genotype are obtained. Deep learning has already been used for the development of image analysis software (RootPainter) and this may be further developed. The main goal will be to use deep learning approaches to link root phenotyping data to the root activity measures, and ultimately to general genotype performance and yield in RadiMax and in field testing, and if possible, directly to genetic data. A further task will be to identify the root traits being of main importance for the prediction of root and crop performance.
The researcher should have demonstrated research experience with state-of-the-art deep learning methodology, preferably of multi-modal data. Experience with phenotyping and demonstrated interest in inter-disciplinary research is desirable.
The position is open from June 1, 2021 or as soon as possible thereafter.
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Further information on the Department is linked at http://www.science.ku.dk/english/about-the-faculty/organisation/. Inquiries about the position can be made to Erik Dam ([email protected]).
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 Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.
The starting salary for a post doc is currently up to DKK 437.843 including annual supplement (+ pension up to DKK 74.871). Negotiation for a salary supplement is possible.
The application, in English, must be submitted electronically by clicking APPLY NOW below.
Please include
The deadline for applications is 1 March 2021, 23:59 GMT + 1.
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 http://employment.ku.dk/faculty/recruitment-process/.
Kilde: Jobnet.dk
The job
Being employed at the Department of Computer Science (DIKU), you will be part of our interdisciplinary team of researchers from DIKU and the Department of Plant and Environmental Sciences. At DIKU, you will be part of and collaborate with colleagues in the Machine Learning section and the SCIENCE AI Centre. DIKU is ranked 25 on the 2019 Shanghai world ranking for computer science / engineering departments.
The researcher will develop machine learning methods for analysis of multi-modal time series data. The project will focus on data from the RadiMax facility at PLEN including sub-soil root images, drone field images, genetic data, environment observations, and interventional parameters.
The overall research goal is to use deep learning approaches to exploit data from root phenotyping in the RadiMax facility for improved plant breeding towards plant genotypes with deep and efficient root growth. In the studies in the facilities, hundreds of genotypes of wheat, grasses and potatoes are phenotyped for deep root growth and other traits, and 1000 root images per genotype are obtained. Deep learning has already been used for the development of image analysis software (RootPainter) and this may be further developed. The main goal will be to use deep learning approaches to link root phenotyping data to the root activity measures, and ultimately to general genotype performance and yield in RadiMax and in field testing, and if possible, directly to genetic data. A further task will be to identify the root traits being of main importance for the prediction of root and crop performance.
The researcher should have demonstrated research experience with state-of-the-art deep learning methodology, preferably of multi-modal data. Experience with phenotyping and demonstrated interest in inter-disciplinary research is desirable.
The position is open from June 1, 2021 or as soon as possible thereafter.
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Further information on the Department is linked at http://www.science.ku.dk/english/about-the-faculty/organisation/. Inquiries about the position can be made to Erik Dam ([email protected]).
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 Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.
The starting salary for a post doc is currently up to DKK 437.843 including annual supplement (+ pension up to DKK 74.871). Negotiation for a salary supplement is possible.
The application, in English, must be submitted electronically by clicking APPLY NOW below.
Please include
- Curriculum vitae
- Diplomas (Master and PhD degree or equivalent)
- Research plan – description of current and future research plans
- If available, description and documentation of teaching and supervision experience and qualifications - please describe and document:
- Experience with supervision of BSc and MSc students
- Teaching experience
- Formal pedagogical training
- Complete publication list
- Separate reprints of up to 5 particularly relevant papers
The deadline for applications is 1 March 2021, 23:59 GMT + 1.
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 http://employment.ku.dk/faculty/recruitment-process/.
Kilde: Jobnet.dk
Information og data
Denne ledige stilling har jobtypen "Forsker", og befinder sig i kategorien "Sundhed og forskning".
Arbejdsstedet er beliggende i København Ø.
Jobbet er oprettet på vores service den 10.2.2021, men kan have været deaktiveret og genaktiveret igen.
Dagligt opdateret: Dette job opdateres dagligt ud fra jobudbyderens hjemmeside via vores søgemaskineteknologi og er aktivt lige nu.
- Forsker
- København Ø
- Torsdag den 01. april 2021
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