BEMÆRK: Ansøgningsfristen er overskredet
Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Quantitative Genetics and Genomics programme. The position is available from 01 February 2024 or later.
Title:
PhD in Deep Learning for Biodiversity Monitoring: Custom Imaging Platform and Deep Learning to Classify and Phenotype Earthworms
Research area and project description:
This exciting PhD opportunity aims at developing novel imaging methods and deep learning algorithms to describe and classify earthworms. Although cryptic, earthworms have considerable ecological importance, and this original approach will help understand and protect them. It is the first part of a larger 5-year project that uses novel technologies (imaging, acoustics, deep learning, remote sensing, etc) to monitor and understand earthworms better.
Context:
Our food system ultimately rests on soils, which we are losing at an alarming rate. To counteract this trend, we need to transition from an extractive to a restorative and circular agriculture. This change of paradigm must come together with more research on the organisms, such as decomposers, that enact circularity – which have so far been severely understudied. Amongst these earthworms, with their unmatched ubiquity and biomass, are pivotal actors. However, these animals live below ground, making their study a methodological challenge: they are very difficult to observe and monitor. However, recent technological developments in remote sensing and deep learning represent an unprecedented opportunity to shed new light on these cryptic actors of circularity.
Outcomes:
The successful applicant will develop “the Vermiscope,” a novel open-source hardware based on camera/CCD sensors to acquire standardized and complete high-resolution images of earthworms. After “scanning” a collection of earthworms to generate groundtruth data, the candidate will implement a new deep learning algorithm, “Deep Worming,” that represents animals in a “segment space” and classifies them by modeling the “grammar of their segments.” This project will produce both conceptually novel (hardware and software) methods and tools for ecologists, farmers and citizen scientists, which paves the way to using novel technology to understand these hidden creatures.
Research Group:
The successful student will be integrated the growing Digital Approaches for Resilient and Sustainable Agriculture (DARSA) group, started in 2022, at the Center for Quantitative Genetics and Genomics (QGG). Both the group and the centre are inclusive and multidisciplinary environments with a range of local and international collaborations. The research takes place at Aarhus University, a world-leading institution located in a vibrant city.
Project description: For technical reasons, you must upload a project description. Please simply copy the project description above, and upload it as a PDF in the application.
Qualifications and specific competences:
- Hold a Master's degree in data science, mathematics, physics, computational biology or another quantitative field
- Be at least familiar with deep learning, image processing and general database architecture
- Have strong programming skills (in particular, experience working with scientific languages (e.g. R, Python) and packages (e.g. Pytorch, Tensorflow, Scikit-learn, Numpy, Pandas and OpenCV)
- Have an interest in digital and sustainable agriculture and ecology
- Be fluent in English (written and spoken)
- Demonstrate advanced collaborative and interpersonal skills
Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is C. F. Møllers Allé 3, 8000 Aarhus C, Denmark.
Contacts:
Applicants seeking further information are invited to contact:
- Professor Torben Asp, torben.asp@qgg.au.dk
- Assistant Professor Quentin Geissmann, qgeissmann@qgg.au.dk
How to apply:
Please follow this link to submit your application. Application deadline is 30 September 2023 at 23:59 CEST. Preferred starting date is 1 February 2024.
For information about application requirements and mandatory attachments, please see our application guide.
Please note:
- The programme committee may request further information or invite the applicant to attend an interview.
- Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.
Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.
INFORMATIONER OM STILLINGEN:
- Arbejdspladsen ligger i:
Aarhus Kommune
-Virksomheden tilbyder:
-Arbejdsgiver:
Aarhus Universitet, Nordre Ringgade 1, 8000 Aarhus C
-Ansøgning:
Ansøgningsfrist: 30-09-2023; - ansøgningsfristen er overskredet
Ved skriftlig henvendelse: https://app.researchplanner.net/Peoplexs22/CandidatesPortalNoLogin/ApplicationForm.cfm?PortalID=16581&VacatureID=1083041
Se mere her: https://job.jobnet.dk/CV/FindWork/Details/5854774
