International PhD Fellowships in AI Inspired Molecular Communications Technology

Communicable diseases remain a major global public health threat worldwide. A timely example is the COVID-19 pandemic, which has brought the world to an unprecedented standstill, with more than millions confirmed infected and hundred thousands lives lost This crisis motivates the quest for new approaches to monitor and treat viruses with high spread potential, to rapidly and efficiently silence them. Here we propose a tool capable of rapidly testing the effect of new viruses in human tissues and of providing rapid response to viral agents.

Our project will develop a technology platform where engineered cell-structures, known as bio-nanomachines, can be controlled by radio frequency (RF) signals to release, control, navigate and uptake therapeutic molecules to silence viral infections. These therapeutic molecules, miRNAs, carried by exosomes, can silence cells infected by virus.

PhD Project 1 is on "Artificial intelligence-driven externally controllable radio frequency system" to advance by breakthrough RF-antennas targeting dielectric properties of cells and cell culture media with bio-nanomachines with disruptive modes of beamforming, spatial, temporal, and frequency diversity, antennas in an array and functional nanoparticles used as active low-frequency nanoantennas.

PhD Project 2 is "Artificial intelligence inspired molecular communications" is to predict behaviour of viral propagation. This prediction will be integrated with molecular communication simulation tools, which will integrate biophysical and statistical mechanic properties of the virus.

We seek a highly-motivated individual holding a master’s degree in signal processing, wireless communication, electromagnetics, information theory, biophysics, applied mathematics, or other relevant disciplines. A strong mathematical background and a research-oriented master thesis within one of these areas is expected. Further, the applicant must have experience with programming and willing to learn new topics like nanoscale molecular communications using optical and quantum theories. Publication activities in the aforementioned disciplines will be considered an advantage. Motivation for fundamental scientific research of practical relevance is essential. The candidate is expected to deliver min 3 journal articles within the duration of the project. The applicant should have good communication skills and be willing to collaborate with other researchers in the cross-disciplinary group of people connected to this project.

Prerequisites: MSc in electrical engineering with course credits in information- and communication theory, signal processing, communication networks, and stochastic modeling and optimization. MSc in biophysics with solid course background in information- and communication theory, signal processing, communication networks, and stochastic modeling and optimization are welcome to apply for the position.

Applicants who do not master a Scandinavian language must provide evidence of good written and spoken English language skills. The following tests can be used as documentation: TOEFL, IELTS, Cambridge Certificate in Advanced English (CAE), or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:

TOEFL: 600 (paper-based test), 92 (Internet-based test)

IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test accepted)

CAE/CPE: grade B or A.

• Salary NOK 479 600 -- 523 200 per annum depending on qualifications and seniority as PhD Research Fellow (position code 1017)
• Attractive welfare benefits and a generous pension agreement
• Vibrant international academic environment
• Career development programmes
• Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities

Applicants are asked to provide a research statement (max 3 pages) in their application, describing research interests and initial plans with regards to the above project description. The statement should also provide details on how the project relate to previous education, research and competence.