The Section for Medical ICT Research at the Oslo University Hospital has 2-3 fulltime PhD Research Fellows (http://www.ivs.no). This fellowship belongs to “research on bio-nano things for human health — aiming wirelessly connect deep implants/synthetic cells to the Internet” and is funded by the Research Council of Norway project Communication Theoretical Foundation of Wireless Nanonetworks (CIRCLE) and the EU’s H2020 framework FET Open Project Next-generation Theranostics of Brain Pathologies with Autonomous Externally Controllable Nanonetworks (GLADIATOR). The PhD projects involve a cross-disciplinary supervisory team from Department of Electronic Systems (IES), the Norwegian University of Science and Technology and Oslo University Hospital.
The PhD positions will be with Prof. Balasingham’s group – http://www.balasingham.com
Duties and responsibilities
The current wireless communication of in-body sensors is realized using electromagnetic and acoustic waves. Inspired by quantum and celI-to-cell communications, however, recent studies propose using molecules rather than waves. In the field of integrated molecular communication (MC) used to develop bio-nano transceivers for the endocrine system (mediated by hormones, small molecules, and extracellular vesicles (EV) and the nervous system (mediated by electrochemical potential). MC is inherently biocompatible and offers 10 000 times greater energy savings and transmission power on the order of 1pW compared to classical methods. Balasingham et al. proposed using nanomachines to communicate and stimulate a single neuron and showed stimulation by subthreshold activation pulses (extremely low voltage pulse trains). This seminal work will be extended here for stimulating (pacing) cardiomyocytes using synthetic cells — magnetosomes.
PhD projects: EV inspired communication system and simulator development
A realistic physics-based channel model of EV release, propagation, and reception will be developed. This multiscale model includes the cardio-vascular network including the heart conduction system and heart muscle fibers. The model will take into account the intra-ventricular blood flow of the myocardium. We aim to 1) model EVs with respect to the aforementioned communication channel and study their capabilities to carry information as cargo molecules; 2) study the release process using numerical simulations with statistics of molecules and EVs injected into the blood, accounting for the shear stress applied by the blood flow (convection and diffusion) to the molecular mechanism by which the molecule release is controlled; 3) analyze the propagation process w.r.t. ventricle contraction and intra-ventricular flow field — leading to a stochastic channel model with molecular noise which captures the flow, geometry, and position (the latter will be simulated by using a 4D geometry of the cardiac cavities with appropriate models/boundary conditions by using the HEART (electrical/mechanical) models; the blood velocity field will drive the propagation of the molecules); and 4) study the reception process by mathematically deriving the detection probability of pacemaker cells, taking into account the blood pressure and the surface area of the molecule detector.
T1: EV communication system theory: Study synthetic cells, EVs, and propagation in tissues and blood with organ movement and tissue deformation. Expected results will be stochastic models for release and stimulation, propagation, and reception processes.
T2: Information transfer using EVs: Study information encoding, modulation, and channel state information. Derive information theoretical (upper or realistic) bounds in a realistic environment. Estimate information capacity in a multiple input multiple output (MIMO) EV network.
T3: Anomaly detection: Develop a screening technique to detect disease, malfunctioning cells typically found in failing heart – “scar tissue” interrupting the action potential transfer in the heart conduction system and/or with deformed cells in muscle tissues making the heart not to contract and function properly.
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.LEARN MORE