25 phd-in-architecture-and-built-environment Postdoctoral positions at UNIVERSITY OF HELSINKI in Finland
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studies and research work leading to a completed PhD thesis Your work may also include teaching duties (at most 5% of annual working time). Requirements and eligibility criteria For the Doctoral
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environment with a variety of development opportunities and benefits. The annual gross salary range will be approx. €45,000 – €51,000, depending on the appointee’s qualifications and experience. In addition
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doctoral degree relevant for the project, for instance a PhD in plant sciences or plant ecology, and the ability to conduct independent scholarly work. The position also provides the opportunity to co
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collection and/or experimentation. We seek candidates who have completed a PhD in ecology or a related field, have strong conceptual and statistical skills, and experience working with large and complex
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on the research interests of the candidate, there will also be opportunities to complement existing data with additional field data collection and/or experimentation. We seek candidates who have completed a PhD in
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. Should you have any questions, need assistance or adjustments during the recruitment process, please contact phd-positions@helsinki.fi – we’re here to support you. A diverse and equitable study and work
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menu at the top of the page to see detailed instructions. Should you have any questions, need assistance or adjustments during the recruitment process, please contact phd-positions@helsinki.fi – we’re
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. WHAT WE OFFER We are an equal opportunity employer and offer an attractive and diverse workplace in an inspiring environment with a variety of development opportunities and benefits. The annual gross
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information, visit the lab web pages: See also our recent publication: DOI: 10.1038/s41467-024-54445-1 Your qualifications We are looking for ambitious researchers with a PhD, a solid publication record, and
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, including how DNAme potentially drives trait variation and how it responds to the environment. We will use machine learning tools to perform high-throughput phenotyping of birch leaves – specifically stomatal