Postdoc Edge-AI-assisted Advanced Phenotyping

Updated: 4 months ago
Deadline: 31 Jul 2023

23 May 2023
Job Information
Organisation/Company

Delft University of Technology (TU Delft)
Research Field

Technology
Researcher Profile

Recognised Researcher (R2)
Country

Netherlands
Application Deadline

31 Jul 2023 - 21:59 (UTC)
Type of Contract

Temporary
Job Status

Not Applicable
Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Precision agriculture, which employs sensing technology and artificial intelligence to drive automated agriculture processes and decisions, has demonstrated great potential to improve efficiency, transparency, and productivity in the sector. For example, automated crop monitoring in greenhouses can be carried out collaboratively in real time using handheld devices and autonomous robots to collect data and monitor crop health. While AI has shown promise in many context-sensing tasks, realizing the full potential of AI for automated crop monitoring requires overcoming several research challenges. These include designing computationally efficient deep learning solutions for resource-constrained edge devices and addressing the sparse data problem in training robust monitoring systems.

To develop edge computing and AI-assisted solutions for resource-efficient and robust mobile crop monitoring, the Embedded System Group is offering a 4-year Ph.D. position funded by the Dutch National Growth Fund NXTGEN Hightech program. We are seeking a highly qualified candidate to work on this challenging but impactful project. The candidate will be supervised by Dr. Guohao Lan and Prof. dr. Koen Langendoen and collaborate with the TU Delft AgTech Institute and our industry collaborator Sobolt


Requirements
Specific Requirements

The ideal candidate is expected to have the following qualifications:

  • Hold a doctoral degree in Computer Science, Electrical Engineering, or a closely related field;
  • Possess strong skills in system programming and prototyping;
  • Be independent, self-motivated, reliable, and eager to learn and solve practical challenges;
  • Demonstrate knowledge of and a keen interest in deep learning, embedded systems, and edge computing;
  • Willing to work out of the office and collaborate with industry partners;
  • Have excellent English language skills, including proficient writing and presentation abilities;

Additional Information
Benefits

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (based on scale 10: € 2.960,00 - € 4.670,00). The TU Delft offers a customizable compensation package, discounts on health insurance and sports memberships, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, we offer the Coming to Delft Service . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programma f or partners and the organise events to expand your (social) netowrk.


Selection process

Are you interested in this vacancy? Please apply before July 31, 2023, via the application button and upload your motivation, transcripts, CV, and reference letters.

  • A pre-employment screening can be part of the selection procedure.
  • You can apply online. We will not process applications sent by email and/or post.
  • Please do not contact us for unsolicited services.

Additional comments

For more information about this vacancy please contact Guohao Lan, Assistant Professor.


Website for additional job details

https://www.academictransfer.com/328154/

Work Location(s)
Number of offers available
1
Company/Institute
Delft University of Technology
Country
Netherlands
City
Delft
Postal Code
2628 CD
Street
Mekelweg 2

Where to apply
Website

https://www.academictransfer.com/328154/postdoc-edge-ai-assisted-advanced-pheno…

Contact
City

Delft
Website

http://www.tudelft.nl/
Street

Mekelweg 2
Postal Code

2628 CD

STATUS: EXPIRED
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