PhD student in Distributed Machine Learning for Next Generation Wireless Communications - Hiring in process/Finished, not possible to apply

The Department of Information Technology holds a leading position in both research and education at all levels. We are currently Uppsala University's third largest department, have around 350 employees, including 120 teachers and 120 PhD students. Approximately 5,000 undergraduate students take one or more courses at the department each year. You can find more information about us on the department of Information Technology website. 

At the Division of Computer Systems, we develop theory and applications of communication systems and computer architecture. Two important goals are to design systems that are energy efficient and secure. The research groups publish at prestigious journals and have collaborations with international academic and industrial partners.

Project Description: Distributed Learning over Wireless Communications
This project aims to deepen our understanding and knowledge base of distributed machine learning and wireless communication systems. Our primary goal is to develop methods that enable distributed machine learning in the next generation of wireless communication systems, specifically targeting applications in vehicular networks and the Internet of Things for 6G. The research will concentrate on devising general distributed learning methods and wireless communication protocols that collaboratively improve communication and energy efficiency, reliability, security, and privacy of the communication.

By combining these domains, we aim to facilitate the development of real-time critical applications that achieve high learning and communication performance. As part of this project, we expect to publish our research results in prestigious journals and conferences to showcase our contributions to the field.

If you are enthusiastic about exploring new research directions in wireless communications, machine learning, and their integration, and if you are enthusiastic about exploring new research directions in this field, we highly encourage you to apply for this PhD position. By joining our team, you will have the opportunity to contribute to shaping the future of wireless communication systems.

Duties
The duties for this PhD position involve a strong analysis of machine learning, wireless communications, and optimization from both theoretical and practical perspectives. You will be working in a coaching-focused environment where skills on these subjects can readily be improved with help from your advisors, fellow PhD students, and courses. 

The position is for a maximum of five years, and the PhD student is/are expected to devote his/her/their time to research and attendance of courses aligned to the research topic. The rest of the duties involve teaching at the Department, including also some administration, to at most 20%.

Requirements
To meet the entry requirements for doctoral studies, you must

• hold a Master’s (second-cycle) degree in computer science, electrical engineering or applied mathematics, or
• have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including an independent project worth at least 15 credits, or
• have acquired substantially equivalent knowledge in some other way.

As for all PhD students, a genuine interest and curiosity in the subject matter and excellent analytical and communication skills, both oral and written in English, are required. We require that applicants are already good writers and programmers. Moreover, aptitude, self-motivation, and willingness to learn are among the best tools for the job.

The candidate should possess a strong theoretical foundation along with practical experience in either machine learning, wireless communication, or optimization, which will serve as a solid basis for conducting impactful research and making significant contributions to the field. However, it is important to note that the selected PhD student will also receive comprehensive training to acquire any necessary skills that may be lacking, ensuring a well-rounded and capable researcher.

Additional qualifications
Additional qualifications include knowledge on machine learning theory, wireless communication protocols, and optimization techniques. Candidates should possess a deep understanding of the underlying theoretical frameworks and the mathematical foundations that support them, enabling an analysis, design, and evaluation of innovative approaches within the research domain. Moreover, experience in distributed learning and cellular wireless networks is also advantageous.

In addition to theoretical proficiency, candidates should also demonstrate practical experience in applying their knowledge to real-world scenarios. This involves hands-on experience in implementing machine learning algorithms, developing wireless communication systems, or solving optimization problems. Practical skills in programming languages are highly desirable, especially in Python, MATLAB, or Julia.

The applicants should be able to work well both on their own and in collaboration with a diverse group, be comfortable giving and receiving constructive criticism, and have strong abilities for critical thinking and structured work. These competencies are as important as the technical qualifications. Please see the Department's web page for PhD studies for more details.

Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines.

Application
The application should include:
(1) a statement (at most 2 pages) of the applicant’s motivation for applying for this position, including a self-assessment on why would you be the right candidate for this position;
(2) a CV;
(3) degrees and grades (translated to English or Swedish);
(4) the Master’s thesis (or a draft thereof, and/or some other self-produced technical or scientific text), list of publications, online code repositories, and other relevant documents; and
(5) references with contact information (names, emails and telephone number) and (if possible) up to two letters of recommendation.

Applications may be submitted by candidates that have not fully completed the master degree (or equivalent, see requirements above), however, all applicants should state the earliest possible starting date of employment.

About the employment
The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100 %. Starting date 1 April 2024 or as agreed. Placement: Uppsala. 

For further information about the position, please contact: Assistant Professor Jose Mairton Barros da Silva Junior (+46 70 1679794, mairton.barros@it.uu.se).

Please submit your application by 19 January 2024, UFV-PA 2023/4920.

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