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monthly salary is €3,700–€4,000, depending on experience and qualifications. The employment contract includes a six-month probationary period. Staff benefits include occupational health and fitness services
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experience working with administrative firm-level data. The doctoral degree must be granted before the beginning of employment. The work requires independent thinking and problem-solving skills as
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completed a PhD in economics or agricultural economics, who have solid training in econometrics and applied microeconomics and experience working with administrative firm-level data. The doctoral degree must
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facilities, and opportunities for professional development (https://www.helsinki.fi/en/about-us/careers ). YOUR PROFILE PhD in biology, mathematics, or a related field Strong background in mathematical
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collaboration and communication skills Teaching skills necessary for the position Excellent written and spoken English skills Highly valued qualifications: Experience working with highly fragmented genomic data
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the candidate's background and interests, ensuring a collaborative and engaging research experience. We seek candidates who have completed a PhD in ecological statistics or environmental economics or a related
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approach to trainee development and mentorship within the team. Ability to design, execute, and troubleshoot experiments to a high technical standard, with strong data analysis and interpretation skills
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development (https://www.helsinki.fi/en/about-us/careers ). How to apply A response to essential criteria (max 2 pages). Please ensure you provide demonstrated experiences from your previous work in relation
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researchers whose expertise is complementary. Applicants may be primarily experimental or computational. We are especially interested in candidates who can cover a strong combination of skills (not necessarily
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doctoral degree in computer science, digital humanities or a related field, and have a keen interest in multimodality and audiovisual media. Previous experience of applying computational methods to large