Post-doc in Machine Learning for Image Processing on Embedded Devices

Post-doc in Machine Learning for Image Processing on Embedded Devices (V24.0155)

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Job description

We are looking to fill a two-year postdoctoral researcher position as a part of the Northern Netherlands Partnership (SNN) funded project through DigiAgro3 2024. The main goal of the post-doc project will be to develop machine learning models capable of robustly classifying images of agricultural crops based on markers for health state of the crop and deploying those models on a variety of low-power edge devices. The goal of the project is to enable precision farming practices, with a focus on sustainable and robust methods.

We are looking for a highly motivated and independent Postdoctoral candidate with a background in mathematics, machine learning, and/or embedded devices, who is excited to work in an interdisciplinary environment. During your Post-doc, you will work together with our vibrant and interdisciplinary team, which consists of enthusiastic PhD students, Post-docs, and industry partners with backgrounds in machine learning, robotics, sensor technology, embedded devices, as well as agriculture and plant physiology.

Job description
The position is intended for two years with a start date as early as possible, before the end of June 2024. The postdoctoral candidate will conduct research in the field of Machine Learning, Image Analysis, Pattern Recognition, and Embedded AI. The candidate is expected to (i) conduct research related to dataset acquisition of plant images using a variety of camera setups including RGB, RGBI, multispectral, and hyperspectral cameras, (ii) investigate the relevance of each data modality, (iii) develop methods capable of classifying images containing healthy and stressed crops, (iv) adjust the models for deployment on a variety of edge devices, (v) and evaluate the performance of final deployments. The project requires interacting with a large consortium of academic and industrial partners and culminates by demonstrating the final product usable by our industrial partners. This setup provides the opportunity for an impactful and highly dynamic postdoctoral research experience leading to publication of academic research articles while working on an industry-relevant problem of high societal relevance.

Organisation
Since its foundation in 1614, the University of Groningen has enjoyed an international reputation as a dynamic and innovative center of higher education offering high-quality teaching and research. Balanced study and career paths in a wide variety of disciplines encourage currently more than 34,000 students and researchers to develop their own individual talents. Belonging to the best research universities in Europe and the top 100 universities in the world (see our ranking: https://www.rug.nl/(...)ternational-rankings , the University of Groningen is truly an international place of knowledge. Within the Faculty of Science and Engineering (FSE), the Engineering and Technology institute Groningen (ENTEG) conducts engineering science research and covers a broad area of mechanical engineering, electronic materials and MEMS, nanotechnology, control engineering, and robotics.

This current postdoctoral project is a collaborative project between the Discrete Technology and Production Automation (DTPA) group, hosting Dr. Bahar Haghighat, and the Intelligent Systems Group, headed by Prof. Dr. Kerstin Bunte and hosting Dr. Michael Wilkinson. The Embedded AI/ML research thrust within DTPA research group led by Dr. Bahar Haghighat focuses on the development of embedded machine learning solutions that can be deployed on low-power low-memory embedded devices.

Qualifications

• have a PhD degree in Mathematics, Computer Science, Electrical Engineering, or another related field with strong mathematical training
• excellent research qualities, as evidenced by a publication record in international peer-reviewed journals and renowned conferences, and a relevant international network
• a dynamic, respectful, and pioneering professional attitude
• ability to work independently and with colleagues
• strong problem-solving ability
• strong cross-cultural sensitivity and strong communication skills
• able to communicate and teach in English. Knowledge of Dutch is an advantage but not obligatory.

Organisation
Conditions of employment

We offer you in accordance with the Collective Labour Agreement for Dutch Universities:

• a salary from a minimum of € 3,877 gross per month up to a maximum of € 5,090 gross per month (salary scale 10) based on a full-time position and dependent on qualification and work experience
• a holiday allowance of 8% gross annual income
• an 8.3% end-of-the-year allowance
• a position is available for 1 year with a possibility of extension.

Application

Please send your application to us, by submitting the following documents:

• CV which includes a full list of publications
• transcript that shows the grades for all your math modules
• motivation letter (1 page)
• research statement (1-2 pages)
• copy of the PhD diploma or estimated time of graduation
• contact details of 3 academic references.

You may apply for this position until 14 April 11:59pm / before 15 April 2024 Dutch local time (CET) by means of the application form (click on "Apply" below on the advertisement on the university website).

The University of Groningen strives to be a university in which students and staff are respected and feel at home, regardless of differences in background, experiences, perspectives, and identities. We believe that working on our core values of inclusion and equality are a joint responsibility and we are constructively working on creating a socially safe environment. Diversity among students and staff members enriches academic debate and contributes to the quality of our teaching and research. We therefore invite applicants from underrepresented groups to apply. For more information, see also our diversity policy webpage: https://www.rug.nl/(...)rsity-and-inclusion/

Our selection procedure follows the guidelines of the Recruitment code (NVP): https://www.nvp-hrnetwerk.nl/nl/sollicitatiecode

Unsolicited marketing is not appreciated.

Information

For information you can contact:

• Dr Bahar Haghighat, +31 6 25000582, [email protected]

Please do not use the e-mail address(es) above for applications.

Apply