英國馬斯特里赫特大學(xué)2024年招聘博士后（AI驅(qū)動(dòng)型解決方案用于氣候分析和食品安全）

馬斯特里赫特大學(xué)（英文：Maastricht University；荷蘭語：Universiteit Maastricht），一所年輕，且享譽(yù)世界的名校。

作為荷蘭最年輕最國際化的研究型大學(xué)（U類），馬斯特里赫特大學(xué)組建于1974年9月16日，也是荷蘭13所國立研究型大學(xué)之一，是世界大學(xué)聯(lián)盟成員。

馬斯特里赫特大學(xué)以高度的國際化特色著稱，連續(xù)多年被評(píng)為荷蘭國際化程度最高的大學(xué)。馬斯特里赫特大學(xué)商業(yè)與經(jīng)濟(jì)學(xué)院（SBE）是荷蘭乃至歐洲最好的商學(xué)院之一，已取得AACSB、EQUIS、AMBA三項(xiàng)世界頂級(jí)認(rèn)證。

馬斯特里赫特大學(xué)在2024年泰晤士高等教育世界大學(xué)排名中位列第138位 [2]。

PostDoc in AI-driven Solutions for Climate Breakdown and Food Safety

Maastricht University - Institute of Data Science (IDS) / Faculty of Science & Engineering

Job Description

The Institute of Data Science (IDS), a research unit within the Department of Advanced Computing Sciences (DACS) is looking for a post-doctoral researcher to work on the application of data science and AI methods to address the risks of climate breakdown and its impact on food safety, using knowledge representation, reasoning and machine learning. You will join the Ambrosia project which is developing new tools and techniques to support food producers (farmers) and food processors to manage the risks concerning the interaction between climate change and food safety. The focus of the project is on mycotoxins in grains and enteric diseases in horticulture.

As part of the project, there will be the opportunity to collaborate with a number of partners across Europe, including leading research and technology organisations, as well as specialists in AI, machine learning, food safety, climate change and agrifood related information technology. The focus of the research at Maastricht will be on a) the integration of large-scale heterogenous data sets and models concerning climate projections and food safety risks in order to provide concrete advice to food producers and processors, b) applying deductive and non-deductive reasoning methods to help establish predictive and correlative models concerning food safety and climate change.

Of particular interest are candidates with an interest in the application of data science for the climate-agriculture-food-environment nexus writ large. Candidates with experience in climate data, food safety, or agricultural systems are highly encouraged to apply.

You will also be part of a dynamic research environment with access to state-of-the-art facilities and a supportive network of senior and junior researchers working on a wide range of topics in data science and artificial intelligence.

The position responsibilities will include:

Conducting data-driven research in data science, knowledge representation and machine learning/deep learning.

(Co-)authoring scientific, peer-reviewed papers for top conferences and journals. Present your results at conferences and workshops.

Initiating and participating in research proposal writing.

Contributing to department teaching activities, including supervision of PhD and MSc students.

Requirements

We are looking for an ambitious, innovative, and enthusiastic researcher with:

PhD degree in computer science or a closely related field.

Strong computational and data science skills evidenced by peer-reviewed publications.

Experience working with heterogenous datasets, good knowledge of semantic technologies.

Ability to program in Python.

Excellent ability to write, present and communicate in English (C1 level).

What we offer

As PostDoc at Faculty of Science & Engineering, you will be employed by the most international university in the Netherlands, located in the beautiful city of Maastricht. In addition, we offer you:

Good employment conditions. The position is graded in scale 11 according to UFO profile Researcher 3, with corresponding salary based on experience ranging from 歐元4537,00 and 歐元6209,00 gross per month (based on a full-time employment of 38 hours per week). In addition to the monthly salary, an 8.0% holiday allowance and an 8.3% year-end bonus apply.

An employment contract for a period of 2 years subject to annual review. Renewal beyond the initial 2-year appointment possible subject to existence of funding and satisfactory performance. The scope is 1.0 FTE.

At Maastricht University, the well-being of our employees is of utmost importance, we offer flexible working hours and the possibility to work partly from home if the nature of your position allows it. You will receive a monthly commuting and internet allowance for this. If you work full-time, you will be entitled to 29 vacation days and 4 additional public holidays per year, namely carnival Monday, carnival Tuesday, Good Friday, and Liberation Day. If you choose to accumulate compensation hours, an additional 12 days will be added. Furthermore, you can personalize your employment conditions through a collective labor agreement (CAO) choice model.

As Maastricht University, we offer various other excellent secondary employment conditions. These include a good pension scheme with the ABP and the opportunity for UM employees to participate in company fitness and make use of the extensive sports facilities that we also offer to our students.

Last but certainly not least, we provide the space and facilities for your personal and professional development. We facilitate this by offering a wide range of training programs and supporting various well-established initiatives such as 'acknowledge and appreciate'.

Or are you already convinced and ready to become our new PostDoc? Apply now, no later than 5 January 2025 for this position.

Please upload a single PDF document consisting of:

A curriculum vitae that includes the applicant’s publication list.

A maximum two-page research statement that:

Presents the candidate’s expertise directly related to the requirements listed above. Of particular interest are experience with knowledge representation, reasoning, and machine/deep learning. Interest or experience in analysing climate data, food or agricultural data is an advantage.

Describes future research plans in the context of knowledge representation, reasoning and machine/deep learning.

A (co)-authored publication most representative for the job description.

The names and contact details of at least two persons who can provide recommendation letters.

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