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荷兰代尔夫特理工大学2023年招聘博士后(边缘人工智能辅助高级表型分析)

信息来源:荷兰代尔夫特理工大学 | 作者:admin | 时间:2023-07-18 10:20

【简介】博士后招聘网整理分享“荷兰代尔夫特理工大学2023年招聘博士后(边缘人工智能辅助高级表型分析)”,浏览查询更多博士后招聘计划请访问博士后招聘网

荷兰代尔夫特理工大学2023年招聘博士后(边缘人工智能辅助高级表型分析)

代尔夫特理工大学(Technische Universiteit Delft,简写TU Delft)始建于1842年,位于荷兰代尔夫特市,前身为荷兰王国皇家学院,欧洲顶尖工科联盟IDEA联盟战略成员,仅专注于工程技术领域,是荷兰历史悠久、规模庞大的工科院校。

知名校友包括中国科学院院士陈宗基,中国工程院院士严恺,首位诺贝尔化学奖得主雅各布斯·亨里克斯·范托夫,巴基斯坦核计划之父阿卜杜勒·卡迪尔·汗和飞利浦集团创始人杰拉德·飞利浦等。

Postdoc Edge-AI-assisted Advanced Phenotyping

Delft University of Technology

Postdoc Edge-AI-assisted Advanced Phenotyping Apply Now Job 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

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;

Conditions of employment

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (based on scale 10: 欧元 2.960,00 - 欧元 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 for partners and the organise events to expand your (social) netowrk.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

Additional information

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

Application procedure

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.

https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=12348&jobTitle=Postdoc%20Edge-AI-assisted%20Advanced%20Phenotyping

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