Doctoral Position in Deep Learning for Sustainability Science (University of Helsinki Department of Computer Science)

The University of Helsinki (https://www.helsinki.fi/en) is an international scientific community of 40,000 students and researchers. It is one of the leading multidisciplinary research universities in Europe and ranks among the top 100 international universities in the world. The Department of Computer Science (https://www.helsinki.fi/en/computer-science), which is part of the Faculty of Science, is one of the leading Computer Science research and teaching units in Europe. The research themes of the Department cover machine learning and algorithms, computer networks and distributed systems, software systems and bioinformatics. The Department of Computer Science, Faculty of Sciences, University of Helsinki invites applications for a Doctoral Student in Deep Learning for Sustainability Science Position description The Spatiotemporal Data Analysis research group of Associate Professor Laura Ruotsalainen is seeking a PhD candidate to conduct research in the Academy of Finland funded project “Sustainable urban development emerging from the merger of cutting-edge Climate, Social and Computer Sciences (CouSCOUS)”. The candidate will work with city modelling and deep learning methods for predicting traffic flows. The position provides an opportunity to contribute both to groundbreaking data science and sustainability science. The CouSCOUS project answers to the possible challenges on air quality by helping cities to plan climate-healthy future urban areas, considering future traffic flows and population structures. CouSCOUS combines the fields of artificial intelligence, atmospheric and social sciences in a way that has not been done to this extent before and therefore advances the state of scientific research in all disciplines involved and provides decision makers and city planners globally with novel relevant information and tools for creating future sustainable cities. The candidate will join the Spatiotemporal Data Analysis research group (https://www.helsinki.fi/en/researchgroups/spatiotemporal-data-analysis) consisting of 3 other PhD students and 2 Postdocs, with strong links to international computer science, sustainability and navigation societies. The starting date is preferably in February 2021, but negotiable. Requirements The work involves research-related activities, including conducting theoretical and applied research, data analysis, writing research articles, participating in and presenting research at academic conferences, and teaching-related activities. The ideal candidate has a strong background in algorithms, with a focus on machine learning, as well as good programming skills. Simulation, modelling and game engine experience are considered as an advantage. Excellent written and oral communication skills in English are needed. Applicants should have an MSc in computer science, mathematics or a related field. Applicants who do not currently hold a doctoral student status in the Doctoral Programme in Computer Science at the University of Helsinki are eligible to apply, but in the event of hiring, they are expected to acquire the status during the standard 6-month probationary period. Please check at the time of applying that you are able to fill the admission requirements on time from https://www.helsinki.fi/en/research/doctoral-education/eligibility-and-e.... Salary and benefits The position is full-time and funded for two years by the project. After two years, the Professor will help the candidate to apply for funding for an additional two years to finalize the PhD work. For a doctoral student, the starting salary is 2350–2700 euros/month, depending on previous qualifications and experience. The University of Helsinki offers comprehensive services to its employees, including occupational health care and health insurance, sports facilities, and opportunities for professional development. The International Staff Services office (https://www.helsinki.fi/en/university/working-at-the-university) assists employees from abroad with their transition to work and live in Finland. How to apply Please submit your application with the attachments via the University of Helsinki Recruitment System by clicking the ´Apply for the position` button below. The application shall include the following attachments as a single pdf file (in English): • CV with possible publications • Cover letter describing the candidate´s motivation and research interests and especially experience in machine learning, programming and, if applicable, simulation, modelling and game engines. • Contact details of two potential referees who have agreed to provide letters of recommendation The deadline for applications is January 3, 2021. Additional information For more information on the position, please contact the group leader Associate Professor Laura Ruotsalainen laura.ruotsalainen@helsinki.fi For more information on the Doctoral Programme in Computer Science (DoCS), please visit https://www.helsinki.fi/en/research/doctoral-education/doctoral-schools-.... Due date 03.01.2021 23:59 EET If you apply for this position please say you saw it on Engineeroxy

The University of Helsinki (https://www.helsinki.fi/en) is an international scientific community of 40,000 students and researchers. It is one of the leading multidisciplinary research universities in Europe and ranks among the top 100 international universities in the world.

The Department of Computer Science (https://www.helsinki.fi/en/computer-science), which is part of the Faculty of Science, is one of the leading Computer Science research and teaching units in Europe. The research themes of the Department cover machine learning and algorithms, computer networks and distributed systems, software systems and bioinformatics.

The Department of Computer Science, Faculty of Sciences, University of Helsinki invites applications for a

Doctoral Student in Deep Learning for Sustainability Science

Position description

The Spatiotemporal Data Analysis research group of Associate Professor Laura Ruotsalainen is seeking a PhD candidate to conduct research in the Academy of Finland funded project “Sustainable urban development emerging from the merger of cutting-edge Climate, Social and Computer Sciences (CouSCOUS)”. The candidate will work with city modelling and deep learning methods for predicting traffic flows. The position provides an opportunity to contribute both to groundbreaking data science and sustainability science.

The CouSCOUS project answers to the possible challenges on air quality by helping cities to plan climate-healthy future urban areas, considering future traffic flows and population structures. CouSCOUS combines the fields of artificial intelligence, atmospheric and social sciences in a way that has not been done to this extent before and therefore advances the state of scientific research in all disciplines involved and provides decision makers and city planners globally with novel relevant information and tools for creating future sustainable cities.

The candidate will join the Spatiotemporal Data Analysis research group (https://www.helsinki.fi/en/researchgroups/spatiotemporal-data-analysis) consisting of 3 other PhD students and 2 Postdocs, with strong links to international computer science, sustainability and navigation societies.

The starting date is preferably in February 2021, but negotiable.

Requirements

The work involves research-related activities, including conducting theoretical and applied research, data analysis, writing research articles, participating in and presenting research at academic conferences, and teaching-related activities.

The ideal candidate has a strong background in algorithms, with a focus on machine learning, as well as good programming skills. Simulation, modelling and game engine experience are considered as an advantage.

Excellent written and oral communication skills in English are needed.

Applicants should have an MSc in computer science, mathematics or a related field.

Applicants who do not currently hold a doctoral student status in the Doctoral Programme in Computer Science at the University of Helsinki are eligible to apply, but in the event of hiring, they are expected to acquire the status during the standard 6-month probationary period. Please check at the time of applying that you are able to fill the admission requirements on time from https://www.helsinki.fi/en/research/doctoral-education/eligibility-and-e....

Salary and benefits

The position is full-time and funded for two years by the project. After two years, the Professor will help the candidate to apply for funding for an additional two years to finalize the PhD work. For a doctoral student, the starting salary is 2350–2700 euros/month, depending on previous qualifications and experience. The University of Helsinki offers comprehensive services to its employees, including occupational health care and health insurance, sports facilities, and opportunities for professional development. The International Staff Services office (https://www.helsinki.fi/en/university/working-at-the-university) assists employees from abroad with their transition to work and live in Finland.

How to apply

Please submit your application with the attachments via the University of Helsinki Recruitment System by clicking the ´Apply for the position` button below.

The application shall include the following attachments as a single pdf file (in English):

• CV with possible publications
• Cover letter describing the candidate´s motivation and research interests and especially experience in machine learning, programming and, if applicable, simulation, modelling and game engines.
• Contact details of two potential referees who have agreed to provide letters of recommendation

The deadline for applications is January 3, 2021.

Additional information

For more information on the position, please contact the group leader Associate Professor Laura Ruotsalainen laura.ruotsalainen@helsinki.fi

For more information on the Doctoral Programme in Computer Science (DoCS), please visit https://www.helsinki.fi/en/research/doctoral-education/doctoral-schools-....