Postdoctoral fellow within Robot and Sensor Integration
Deadline: 10.01.2022
NMBU has a particular responsibility for research and education that secures the basis for the life of future generations. Sustainability is rooted in everything we do and we deliver knowledge for life. NMBU has 1,800 employees of which about 250 phd scholarships and 6,000 students. The university is divided into seven faculties.
NMBU believes that a good working environment is characterised by diversity.
We encourage qualified candidates to apply regardless of gender, functional ability, cultural background or whether you have been outside the labour market for a period. If necessary, workplace adaptations will be made for persons with disabilities. More information about NMBU is available at www.nmbu.no.
About The Faculty of Science and Technology
The Faculty of Science and Technology (REALTEK) develops research-based knowledge and educates civil engineers and lecturers needed to reach the UN's sustainability goals. We have approximately 150 employees, 70 PhD students and soon 1500 students. The education and research at REALTEK cover a broad spectrum of disciplines.
This includes data science, mechanics and process engineering, robotics, construction and architecture, industrial economics, environmental physics and renewable energy, geomatics, water and environmental engineering, applied mathematics as well as secondary school teacher education in natural sciences and use of natural resources such as in agriculture, forestry and aquaculture. The workplace is in Ås, 30 km from Oslo.
We are looking for a highly motivated postdoctoral fellow to boost research on robotics and smart sensor solutions for food quality assessment directly in the processing lines, throughout the food value chains.
About the position
The Department of Mechanical Engineering and Technology Management, Faculty of Science and Technology at the Norwegian University of Life Sciences (NMBU) has a vacant 2 (two) years Post-Doctoral position related to Robotics and Smart Sensors.
Digital Food Quality (DigiFoods) is a centre for research-based innovation aiming to develop robotic systems and smart sensor solutions for food quality assessment directly in processing lines across all food value chains. The information obtained about food quality will be used to optimize both processes and value chains, making the food industry more efficient and sustainable.
The selected candidate will develop fully autonomous robotic applications and automatic sample preparation, enabling in-line measurement of heterogeneous foods by using industrial robotic systems equipped with smart sensors.
Main tasks
Work on the SFI-DigiFoods, Pillar 2-Robotics, which is divided into two projects:
1 - ROBOSENSE: robotic operation of sensors in industrial food processes;
Enable in-line measurement of heterogeneous foods by robotic control of smart sensors.
1.1 Develop novel in-line sensor systems and applications for measuring critical food quality;
1.2 Develop automation and robotic solutions for enhanced sensor operations in food processes;
1.3 Develop a Minimum Viable Product (MVP) for virtual and real-world testing in industrial scenarios under realistic conditions.
2 - MOBILESENSE: mobile robots for autonomous in-field quality sensing;
Develop fully autonomous robots for automatic collection of large-scale quality data in the field.
2.1 Identify and integrate sensor systems on a mobile robot platform for exploration purposes in open fields;
2.2 Develop autonomous robotic applications for measuring quality features and investigate predicting yield and quality;
2.3 Develop a Minimum Viable Product (MVP) for virtual and real-world testing in agricultural scenarios under realistic conditions.
Competence
Required Academic qualifications
Completed PhD (Equivalent to a Norwegian doctoral degree) within the areas of Robotics, Control and Automation, or Mechatronics Engineering.
Candidates in the process of completing their doctorate are also encouraged to apply, provided the doctorate is completed before starting the position (January 2022).
Proficiency in English, spoken and written.
The following experiences and skills will be emphasized:
A track record of publishing in highly ranked conferences and journals on Robotics, Control and Automation.
Research experience related to design, modeling, analysis, and control of predominantly computer-based automated systems or processes.
Hands-on and practical experience with implementing robotic technology.
Proficiency in simulation software such as Matlab, Gazebo, V-Rep or RViz, with good programming skills in ROS, Python or C/C++, and proven experience in 3D CAD Design program such as Fusion 360, AutoCAD or SolidWorks.
Required personal skills:
Excellent communication and presentation skills.
Ability to work in cross-disciplinary teams.
Desired personal skills:
Ability to design and execute simulations and experimental tests with minimal technical supervision.
Ability to establish cooperation, research, development, and dissemination networks.
Ability to contribute to a good atmosphere in the research group.
Remuneration and further information
The position is placed in government pay scale position code 1352 Postdoctoral Fellow, wage framework 24 (salary grade 59-67) (NOK 534.400-615.800), depending on qualifications. Seniority Promotion in position.
For further information, please contact:
Dr. Antonio Candea Leite, Associate Professor, Faculty of Science and Technology, Norwegian University of Life Sciences, E-mail: antonio.candea.leite@nmbu.no; phone +47 465 69 172.
Dr. Pål Johan From, Professor and Head of the Robotics Group, Faculty of Science and Technology, Norwegian University of Life Sciences, E-mail: pal.johan.from@nmbu.no; phone +47 906 90 932.
To apply online for this vacancy, please click on the 'Apply for this job' button above. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
Application deadline: 10.01.2022.
Up to ten publications selected by the applicant as most relevant must be attached to the application. If it is difficult to identify the contribution of the applicant in multiple-author publications, a short explanation about the applicant’s part of the work is suggested.
Printed material which cannot be sent electronically should be sent by surface mail to Norwegian University of Life Sciences, Faculty of Science and Technology P.O. Box 5003, NO-1432 Ås, within (10.01.2022). Please quote reference number 21/05546.
Applicants invited for an interview will be asked to present verified copies of diplomas and certificates.
