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 Multi-Source Probabilistic Inference (https://www.helsinki.fi/en/researchgroups/multi-source-probabilistic-inf... ) is part of the Finnish Center for Artificial Intelligence (FCAI), and studies statistical machine learning and artificial intelligence methods. We work on fundamental algorithms and methods as well as diverse set of applications.
The Department of Computer Science, Faculty of Science, University of Helsinki invites applications for
1-2 Postdoctoral Researchers in Machine Learning for Ultrasonics
Position description
Ultrasound is broadly used for sensing in industry and medical applications, and can be used also for e.g. cleaning and acoustic levitation. The ultrasound field can be modelled from first principles using forward simulation, but for complex structures this is extremely costly and difficult. We use machine learning (ML) for overcoming this problem, developing advanced ML methods for the field in close collaboration with Electronics Research Laboratory providing the ultrasonics expertise.
We are looking for two postdoctoral researchers to work in this promising area. We ask candidates to express interest on either of two alternative profiles:
The positions are funded by two Academy of Finland projects and are initially until the end of 2023, with possible continuation depending on performance. The starting date is negotiable, but the positions are filled when suitable candidates are found.
The University of Helsinki welcomes applicants from a variety of gender identities, and linguistic and cultural backgrounds.
Requirements
Candidates should have a PhD in computer science or a related field such as statistics, signal processing, or computational physics prior to starting the employment. Candidates currently finalising their degree are also encouraged to apply.
An ideal candidate has a strong publication record in machine learning and can align their past research contributions and interests with the work carried out in the research group. Prior knowledge in ultrasonics is not required but expertise in physics is in general considered an asset.
Salary and benefits
The position is full-time and initially until the end of 2023.The salary is determined based on the university salary system, and will typically be 3,300-3,800 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 University provides support for internationally recruited employees with their transition to work and life in Finland. For more on the University of Helsinki as an employer, please see https://www.helsinki.fi/en/about-us/careers .
How to apply
Please submit your application using the “Apply for the position” link below. The application shall include the following attachments as a single pdf file (in English):
- A CV and a list of publications
- A motivation letter describing your interests and desired research topics within the project
- One or more reference letters, or contact details for possible recommenders
The deadline for applications is May 9th, 2022.
Additional information
For more information on the position, please contact Associate Professor Arto Klami ([email protected] )
The University of Helsinki reserves the right for justified reasons to leave the position open, to extend the application period and to consider candidates who have not submitted applications during the application period.
Due date
09.05.2022 23:59 EEST
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