Doctoral Researcher (Embedded Device Friendly Machine Learning Methods for the Security, Privacy-Preserving of Distributed Data), 2 positions / Väitöskirjatutkija, 2 tehtävää

Tampere University and Tampere University of Applied Sciences create a unique environment for multidisciplinary, inspirational and high-impact research and education. Our universities community has its competitive edges in technology, health and society.

Communications Engineering and Radio Systems Group at the Faculty of Information Technology and Communication Sciences is an internationally recognized research and competence centre with 8 professors and some 70 researchers, all focusing on fundamental basic science and applied research related to different wireless systems and networks. We develop new technology, e.g., for 5G and 6G mobile cellular networks, joint sensing and communications, IoT, intelligent machine and Industrial Internet applications, including new algorithms, hardware, protocols and networking solutions. Our yearly external project volume is around 4 MEUR, and we actively collaborate with global industry and academia. 

Project (Job) description

With the overall general tendency of population ageing and simultaneous shortage of personnel in the healthcare sector, the use of various types of sensors in residential environments for modelling resident activity and consequently inferring potential health or wellbeing issues of residents has been studied widely. Successful modelling and detection of resident activities can reveal information related to active and rest periods, walking patterns, possible hand/arm tremor and body gestures that can be signals of chronical medical conditions such as depression, Parkinson’s disease, diabetes, dementia and so forth. Despite the promise of improving wellbeing, the use of residential sensor data for healthcare purposes also raises serious concerns related to privacy and data security due to the use of imaging, voice recording, potential security compromises of data centres and inference attacks. Also, misdiagnosis caused by false detections or inaccurate models is a concern when relying on automated sensing for healthcare.

SPHERE-DNA project is committed to improving the security and privacy levels of distributed sensing systems used in residential environments. SPHERE-DNA leverages local differential privacy federated learning (LDP-FL) to achieve resilience against data theft and inference attacks, and also uses edge computing to avoid sensitive information transfers to remote servers. SPHERE-DNA relies on multimodal sensor technology and formulates sensor fusion as a machine learning problem that is studied together with security architectures. Hardware acceleration and approximate computing schemes will be studied to enable the deployment of the developed privacy-preservation schemes to lightweight processors and unstable networks of residential environments. SPHERE-DNA accelerates extending health condition monitoring from hospitals to homes, leading to early diagnosis and intervention, and directs healthcare towards an economically sustainable direction.


Essential Requirements (for PhD 1): The candidate should have a MSc degree (or near MSc completion) in computer science, electronics, mathematics, information technologies; knowledge and research/work experience in machine learning, mathematics, computer vision, sensing data inferring, signal processing and database systems, preferably also cybersecurity; high proficiency in programming (e.g. Python, MATLAB, C/C++, TensorFlow); excellent academic track record; available English test certificate; good technical and academic writing and presenting skills;  eligibility for PhD studies in the DPCEE programme at Tampere University.

Essential Requirements (for PhD 2): The candidate should have a MSc degree (or near MSc completion) in computer engineering, electronics, automation engineering, communications engineering, computer science, information technologies;knowledge and research/work experience in FPGA or digital circuit design, processor microarchitecture, machine learning, cloud/edge computing, preferably also cybersecurity; high proficiency in hardware and low-level software design (e.g. VHDL/Verilog, C/C++/Python); excellent academic track record; available English test certificate; good technical and academic writing and presenting skills; eligibility for PhD studies in the DPCEE programme at Tampere University.

Desired Requirements (for both PhDs): proficient oral English, open-minded in multiple culture environments and international research community, good interpersonal skills, ability to supervise MSc students, experience of participating in research projects. The successful candidate needs to apply for and be granted a study right for a doctoral degree in the doctoral program of Computing and Electrical Engineering at Tampere University. 

Tampere University is a unique, multidisciplinary and boldly forward-looking, evolving community. Our values are openness, diversity, responsibility, courage, critical thinking, erudition/bildung, and learner-centredness. We hope that you can embrace these values and promote them in your work.

We offer

The positions will be filled for a fixed-term period ending on 31 December 2024. We expect the qualified candidates start as soon as possible based on mutually agreed start date. A trial period of six months applies to all our new employees.

The salary will be based on both the job requirements and the employee's personal performance in accordance with the Finnish University Salary System. According to the criteria applied to teaching and research staff, the position of a doctoral researcher is placed on level 2-4 of the job requirements scale. The salary of the Doctoral Researcher follows the university policy (typical range 29,000~32,000 EUR per year depending on the phase of doctoral studies and research). A typical starting salary for a Doctoral Researcher is 2500 EUR per month. The salary increases based on experience and the progress of doctoral studies.  

We offer a wide range of staff benefits, such as occupational health care, flexible working hours, excellent sports facilities on campus and several restaurants and cafés on campus with staff discounts. Please read more about working at Tampere University.

Communications Engineering and Radio Systems is recognized as a leading-edge research area of Tampere University. We offer a world-class research environment in internationally recognized research groups. We have strong collaborative networks and offer great opportunities for researchers to develop their careers in an international setting.

How to apply

Please submit your application through our online recruitment system (link below). The closing date for applications is 5th of August 2022 (at 23.59 EEST / UTC+3). Please write your application and all accompanying documents in English and attach them in PDF format.

Applications should include the following documents:

  • Curriculum Vitae according to TENK guidelines
  • List of publications according to Academy of Finland guidelines
  • Reference letters from two people
  • Motivation letter (incl. research directions): 
    • Please clearly say which PhD position you are applying for (PhD1 or PhD 2). 
    • 1-2 pages where you introduce yourself and present your qualifications. 
    • Previous research fields and main research results. 
    • Future goals and research focus.
  • BSc and MSc degree certificates
  • Undergraduate and postgraduate transcripts

For more information, please contact:

Enquiring of PhD 1 please contact Assistant Professor Bo Tan, tel. +358504771867,

Enquiring of PhD 2 please contact Professor Jari Nurmi,  


Tampereen yliopisto ja Tampereen ammattikorkeakoulu muodostavat yhdessä Suomen toiseksi suurimman monitieteisen, innostavan ja vaikuttavan tutkimus- ja oppimisyhteisön. Korkeakouluyhteisömme osaamiskärjet ovat tekniikka, terveys ja yhteiskunta. Lue lisää:

Tampereen yliopiston informaatioteknologian ja viestinnän tiedekunnan Tietoliikennetekniikka ja radiojärjestelmät -tutkimusryhmä etsii kahta väitöskirjatutkijaa Suomen Akatemian projektiin.

Tietoturvallinen ja yksityisyyden säilyttävä terveydenseuranta kotiympäristössä hajautettua dataa ja tekoälyä hyödyntäen (SPHERE-DNA) -projektin tavoite on parantaa asuinympäristössä käytettävien hajautettujen terveydenseurantajärjestelmien tietoturvaa ja yksityisyyden suojaa. Projekti hyödyntää paikallisen differentiaalisen yksityisyyden ja hajautetun oppimisen yhdistelmää (LDP-FL) suojaamaan arkaluontoista dataa vuodoilta. Projektissa käytetään myös reunalaskentaa raakadatan siirtojen välttämiseen. SPHEREDNA tukeutuu monimuotoiseen dataan havainnointivaiheessa, ja käyttää tekoälyä yksittäisten datalähteiden yhdistämiseen. Koneoppimisen ja approksimaatiolaskennan teknologioita kehitetään nopeuttamaan turvallisuuteen ja yksityisyyden suojaan liittyen reunalaskennan ja epävakaiden tietoverkkojen kontekstissa. SPHERE-DNA nopeuttaa pitkäaikaisen terveysseurannan siirtymistä sairaalasta asuinympäristöihin, mikä edesauttaa sairauksien varhaista diagnosointia ja niihin puuttumista, ja ohjaa terveydenhuoltoa taloudellisesti kestävään suuntaan.


Lue tarkemmat tiedot tehtävistä ja hakuohjeet yllä olevasta englanninkielisestä ilmoituksesta.

Jätäthän hakemuksesi yliopiston sähköisellä hakulomakkeella (linkki löytyy tämän ilmoituksen alta).

Hakuaika tehtäviin päättyy 5.8.2022 klo 23.59.

Application period starts: 2022-06-23 13:30Application period ends: 2022-08-05 23:59