博士招生 | 瑞典中部大学招收岗位制博士，资金充裕氛围好，6月入职！
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目前，瑞典中部大学开设了一系列的本科、硕士以及博士研究生课程，供本国和国际学生选择申请，其中每年都会常规开放招生的有全英文授课的本科和硕士研究生专业，专业涉及领域包括：人类学、社会科学、科技、自然科学、教师培训以及健康与护理科学等，课程设置与教学内容非常丰富，并与时代紧密接轨。
招生概要
研究方向为机器学习在嵌入式低功耗领域的应用。组内氛围良好，导师每周开会，有很强的欧洲范围内的合作关系。导师是仪器测量领域内多本期刊的编辑，是IEEE senior member。发文多在mdpi sensors, ieee access, ieee sensors, ieee trans on on instrumentation and measurement。组内资金充裕，每个月博士起始工资28100瑞典克朗，发放办公用品（手机，电脑），有独立工位。申请截止日期：2022年3月31日Are you looking to get a PhD in electronics engineering? Then you might be interested to hear that my research group is currently looking for a PhD student with a focus on embedded machine learning. A lot of exciting things have happened in the last years forming the field of TinyML that allows to run machine learning models on low-power microcontrollers. If you want to be part of this exciting development, apply for our position by 2022-03-31.
项目简介
The Department of Electronics Design
Machine learning has in recent years gained in attraction as a tool for data analysis and data-driven modelling. In an industrial setting, for example, it can be used to evaluate the condition of a machine, or predict the failure of a component based on sensor data. Currently, however, the data analysis is in most cases performed offline, that means at a location different from that where the sensor data is acquired. Due to bandwidth limitations, security concerns, and real-time requirements, amongst others, it is desirable to bring the data analysis closer to the data source. This means that it is desirable to run the machine learning algorithms on embedded systems with constrained resources.
This PhD position focuses on machine learning for energy-constrained embedded systems, such as wireless sensors operated on batteries or energy harvesting sources. During your PhD studies, you will contribute to a better understanding in this domain, investigating current machine learning methods on low-power microcontrollers or alternative low-power computing architectures. You will be analysing energy requirements and limitations, as well contributing to the development of novel and enhanced approaches. As a result, you will contribute to an exciting young field of research, and acquire an attractive competence relevant for both academia and industry.
As a PhD student in the Autonomous Sensor Systems group, you will be a vital part of the research group, collaborating with other PhD students, post-docs and senior researchers. Your studies will consist of courses and own research work, developing your competences through theory and experiments. You are expected to bring forward own ideas in the development of your research agenda, and to contribute to the publication and presentation of results. The research group, in turn, will provide a forum for discussion, supervision and assistance during your studies, supporting your research and career development. You will be part of a leading group in the field of low-power sensing systems and be able to exploit the group’s large international network.
导师介绍
Sebastian's teaching is centered around education in embedded systems, with, amongst others, course responsibility for a basic level course on embedded system programming, and an advanced level course on sensor networks. He is also involved in teaching activities on scientific writing and regularly supervises students in engineering and research projects, as well as BSc and MSc thesis works.
招聘要求
To be considered for a PhD position, the applicant must meet the entry requirements for admission to Mid Sweden University´s third-cycle programme. In order to meet the entry requirements the applicant must have a second-cycle degree, or have completed at least 240 ETCS credits of which at least 60 credits should be second-cycle courses. An additional requirement is that 90 credits of the 240 total must consist of courses in electrical engineering, electronic engineering, or computer engineering, or other closely-related subjects. The applicant is also eligible for consideration if s/he has acquired the corresponding knowledge in some other way.
Apart from the formal entry requirements, the selection will be based on previous experience (i.e., thesis work, projects, internships), relevance of previous educational programmes and courses, results of previous studies, and an interview with the applicant.
We see it as an advantage if you have previous experience with machine learning and embedded systems. For this position, you should also enjoy programming and have an experimental approach to solving problems. Personal qualities such as teamwork skills, initiative, and suitability for PhD studies will be weighted together with your knowledge, competences and experiences in the subject area of this position.
申请方式
申请渠道链接
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