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Postdoctoral Fellowship in Machine Learning and Landscape Analysis 2020, Lund University, Sweden

Lund University


Deadline:

January 01, 2020


Opportunity Cover Image - Postdoctoral Fellowship in Machine Learning and Landscape Analysis 2020, Lund University, Sweden

Postdoc in Machine Learning and Landscape Analysis

 

Humanities and Theology, Department of Archaeology and Ancient History

 

Lund University was founded in 1666 and is repeatedly ranked among the world’s top 100 universities. The University has 40 000 students and 7 600 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

 

The Joint Faculties of the Humanities and Theology have nine departments and carries out large and varied work within research and education with the purpose to understand people as cultural and social beings. The faculties have some 700 employees and around 4000 students. 

The Department of Archaeology and Ancient History at Lund University is one of the oldest and largest archaeology departments in Sweden, and one of the top 100 in the world according to the QS World University Ranking. We provide a lively environment for research and teaching and have done so since 1805.

The department covers four subjects: Classical Archaeology and Ancient History, Archaeology, Historical Archaeology and Historical Osteology. The subjects cooperate with each other, while having different backgrounds with respect to history of ideas and are working partly with different source materials, methods and theoretical perspectives. This is the department’s strength from both a research and education perspective. Our students therefore often choose to combine our different subjects in their studies in order to obtain a personalised degree.

Lund University hereby invites applications for a two-year appointment as postdoc in Machine Learning and Landscape Analysis based at the Department of Archaeology and Ancient History. The successful candidate will work on the project Artificial Intelligence and Landscape Interpretation; Expanding Methods and Challenging Paradigms. The purpose of the project is to use deep-learning methods to analyse aerial and satellite images with the aim of finding archaeologically interesting traces or remains. RGB, multispectral and LIDAR images will be used in the analysis. The person we are looking for has a PhD in computer science, mathematics, physics or a corresponding area, with a specialisation in machine learning and image analysis. The position is based at the Department of Archaeology and Ancient History, but the work will be conducted in close cooperation with the Department of Astronomy and Theoretical Physics.

Duties
The appointee is expected to be able to work independently, but also to cooperate with other researchers within the subject. The postdoc is to participate in, and contribute to, the research environment by, among other things, actively participating in the research seminars and other research-related activities going on within the subject and thereby stimulating the theoretical discussion, contributing their own studies in the area, and contributing to the joint work of initiating new research ideas. The postdoc is expected to conduct their own research mainly at the workplace in Lund. Teaching, supervision and other teaching-related duties may occur within the framework of the appointment, but to a maximum of 20% of working hours.

Qualifications
A person qualified to be appointed as postdoc has, no earlier than three years before the end of the application period, been awarded a PhD or an international qualification deemed to correspond to a PhD. If the degree has been awarded earlier, certification regarding parental leave, illness or similar is to be submitted in conjunction with the application. Very good and documented English language skills is a requirement.

Assessment criteria
The expertise to develop and complete high-quality research, and teaching expertise. In the appointment of the postdoc, research expertise is considered to be particularly important. As a basis for the assessment of the applicants’ qualifications, the applicant is to enclose a research plan for the research that is intended to be conducted within the period of employment. Only applicants whose research plan and previous work can strengthen the research environment are to be considered for appointment as postdoc.

Other requirements
- good programming knowledge, particularly regarding machine learning 
- experience of machine learning and deep-learning concerning image analysis

Specific additional qualifications (in order of priority)
- documented good ability regarding cooperation 
- documented interest for, and experience of, interdisciplinarity
- documented interest for, and experience of, developing research in different environments

The application is to contain the following:
• a signed complete curriculum vitae (CV) and attested copy of the PhD degree
• list of publications (including DOI, ISBN or ISSN numbers)
• a signed plan, maximum 1 500 words (excluding literature lists), of the research project the applicant intends to conduct during the period of employment.

The research plan is to contain a description of:
• aim and research question 
• theory and method 
• relation to the international research front including the most important international work in the field of research 
• schedule and expected results 
• the applicant’s capacity and expertise to conduct the project.

Note: The applicant is responsible for ensuring the application is complete in accordance with the instructions above, that everything has been scanned (as a single PDF file) and that the University receives the application by the application deadline via the recruitment portal.

The appointment is a fixed-term position for a maximum of two years and is full time in accordance with “Agreement on fixed-term employment as a postdoc” between labour market parties dated 4 September 2008 (Swedish Agency for Government Employers, OFRs, SACO-S and SEKO).


Eligible Countries
Host Country
Study Levels
Opportunities
Publish Date
November 18, 2019




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