PhD position in data security in distributed machine learning - Hiring in process/Finished, not possible to apply

Electrification and digitalisation are among the largest areas for the future in the conversion to sustainable societies. The Department of Electrical Engineering conducts successful research and education in these areas - renewable energy sources, electric vehicles, machine learning and wireless sensor networks as well as smart electronic sensors and medical systems. The Department of Electrical Engineering is an international workplace with around 140 employees that all contribute to important technical energy and health challenges at the Ångström Laboratory.

The position will be at the Division of Signals and Systems, at the Department of Electrical Engineering. 

Here you will find a stimulating work environment with a network of Ph.D. students and many interesting projects. The Division of Signals and Systems collaborates with Swedish companies as well as the public sector. We are looking forward to your application. Join us and build the future together with us!

Read more about our benefits and what it is like to work at Uppsala University

Project description
Machine learning is becoming a key component in many modern devices and services, ranging from personal mobile devices to autonomous vehicles or smart grids. To improve the underlying machine learning models, it is often crucial that devices share data among each other or with a central authority. This raises several privacy and cybersecurity issues and it must be ensured that both user data remains safe and that user’s privacy is ensured. In this project, we investigate how these challenges can be addressed using modern privacy-preserving approaches such as federated learning, differential privacy and machine learning using encrypted data.

Duties
The main duties of this position are to conduct basic as well as applied research in the area of distributed machine learning. Particular focus will be on the development and analysis of distributed inference methods for dynamic systems that ensure data security, for example using federated learning, differential privacy, and homomorphic encryption. The duties also include algorithm implementation in Python and C/C++ as well as collaboration with industry partners.

The duties also include teaching and other departmental duties (no more than 20 %).

You will designed the work together with the research team You will be supervised by at least two supervisors. The Department of Electrical Engineering also gives a salary supplement in addition to the local guidelines for doctoral students at Uppsala University.

Requirements

• A master’s degree in engineering physics, electrical engineering, or computer science.
• Specialization in signals and systems (signal processing and control theory), machine learning, or computational science.
• Strong background in applied mathematics with a focus on stochastic processes, time series analysis and statistical inference methods. Alternatively, a background in cryptography.
• Basic knowledge of programming in Python and C/C++.
• Very good oral and written proficiency in English.
• Personal qualities such as good collaboration and communication skills. You should be purposeful, structured and be able to work effectively both individually and in groups.

Merit

The following qualifications are considered a merit but not strictly required:

• Knowledge of cryptography
• Knowledge of Bayesian inference methods
• Oral and written knowledge of Swedish

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

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

For further information about the position, please contact:

Biträdande universitetslektor Roland Hostettler, e-mail: roland.hostettler@angstrom.uu.se, tel.: 018-471 3265 eller Professor Subhrakanti Dey, e-mail: subhrakanti.dey@angstrom.uu.se, tel.: 018-471 7059.

Please submit your application by Janauari 6th 2023, UFV-PA 2022/3753.

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