Uppsala universitet, Institutionen för organismbiologi

The Department of Organismal Biology teaches and explores the evolution, development and function of whole organisms. For more information see www.iob.uu.se

The program for Evolution and Developmental Biology is looking for a new doctoral student, main supervisor P. E. Ahlberg.

Duties/Project description: Over the past decade, tomographic data sets generated by synchrotron microtomography have become increasingly important as a tool for studying the vertebrate fossil record – not least in relation to the origin of tetrapods (land vertebrates). However, these data sets also present novel challenges. They are very large, at least several gigabytes, and while the images are of exceptional clarity and sharpness the brightness contrast between bone and surrounding rock is often low. Because of this low contrast, currently available segmentation software (used to turn the scan data into three-dimensional models of the fossils), which uses brightness thresholds to distinguish structures, often struggles to cope with the data. The paradoxical result is a data set that the human eye can easily interpret, but which is almost impossible to segment except by painstakingly hand-drawing the outlines of the bones – an extremely time-consuming process that creates such a severe bottleneck as to render some synchrotron microtomography data sets effectively unusable.

This project will investigate the potential of Machine Learning as a tool for segmenting such data sets. The hope is that AI image analysis will allow the software to distinguish bone from rock using the same criteria – texture, positional continuity between slices, etc. – that the human eye does. Two already-generated data sets will be used for the project, one relatively easy with quite good brightness contrast (skulls and jaws of the lobe-finned fish Polyplocodus), and one more challenging with very low contrast (blocks of a bone bed from Siberia). Both date to the Late Devonian period and are potentially informative about the origin of tetrapods.

The PhD student will pursue two parallel tasks: developing AI software for automated segmentation of the data sets, and interpreting and describing the fossils based on the segmentations. The student will also evaluate the significance of the fossils with regard to the evolution of the tetrapod lineage (chiefly Polyplocodus) and vertebrate biogeography of the Late Devonian (chiefly the Siberian bone bed).

In order to give sufficient and appropriate support to the student, she/he will have two main supervisors. Per Ahlberg will be principal supervisor, providing expertise on Devonian vertebrates and supplying the data sets. The first co-supervisor will be Thomas Schön (Department of IT, Division of Systems and Control), leading expert on AI analysis of image data and co-applicant on the VR project that is funding this PhD position. Second co-supervisor will be Donglei Chen (Program of Evolution and Development), whose expertise in studying fossil dentitions using synchrotron microtomography will be helpful for the Polyplocodus work.

Requirements: A master degree (or equivalent) in a relevant subject area is required. First-hand experience of segmenting synchrotron microtomography data sets of fossils, ideally both with a conventional software package such as VGStudio or Mimics and with the AI-assisted software package Dragonfly, is essential. The candidate must be fluent in spoken and written English.

Additional qualifications: Other experience of working with vertebrate fossils is desirable. In filling this position, the university aims to recruit the person who, in the combined evaluation of competence, skills and documented qualifications, is judged most suitable to carry out and develop the work-in-hand and to contribute to a positive development of the department.

Position: The PhD-student position is a 4-year appointment, and the candidate will primarily devote the time to his/her own research studies. Other departmental work, such as teaching or administration can be part of the position (maximum 20 %). Salary placement is in accordance with local guidelines at Uppsala University. Information about research education can be found at the web site of the Faculty of Science and Technology, http://www.teknat.uu.se/Doktorand/.

Application: The application should include 1) a letter of intent describing yourself, your research interests and motivation of why you want to do a PhD, 2) a short description of your education, 3) a CV, 4) a copy of your master degree and course grades, 5) the names and contact information (address, email address, and phone number) of at least two reference persons, 6) relevant publications (including master thesis). The application should be written in English.

Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines http://regler.uu.se/?languageId=1.

Salary: According to local agreement for PhD students.
 
Starting date: 01-03-2021 or as otherwise agreed.

Type of employment: Temporary position according to the Higher Education Ordinance chapter 5 § 7.

Scope of employment: 100 %

For further information about the position please contact: Per Ahlberg, per.ahlberg@ebc.uu.se.

Please submit your application by 5th of February 2021, UFV-PA 2020/5026.

Are you considering moving to Sweden to work at Uppsala University? If so, you will find a lot of information about working and living in Sweden at www.uu.se/joinus. You are also welcome to contact International Faculty and Staff Services at ifss@uadm.uu.se.

Type of employment Temporary position
Contract type Full time
First day of employment 2021-03-01 eller enligt överenskommelse
Salary Fixed salary
Number of positions 1
Full-time equivalent 100 %
City Uppsala
County Uppsala län
Country Sweden
Reference number UFV-PA 2020/5026
Union representative
  • ST/TCO, tco@fackorg.uu.se
  • Seko Universitetsklubben, seko@uadm.uu.se
  • Saco-rådet, saco@uadm.uu.se
Published 05.Jan.2021
Last application date 05.Feb.2021 11:59 PM CET

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