Jobid=9dd1b38d2088 (0.0168)
ppThis PhD position focuses on developing phase-coherent, AI-enabled data acquisition and system intelligence for Magnetic Resonance Imaging (MRI). /p h3Job description /h3 pMagnetic Resonance Imaging (MRI) is central to modern diagnostics, offering rich contrast in soft tissues and extensive clinical utility. However, a key limitation remains: the long scan times, often 30–40 minutes per patient, due to the weak and spatially complex nature of MRI signals. Each MRI examination involves multiple pulse sequences, with signal acquisition being sensitive to coil placement, sensor geometry, B0/B1 inhomogeneities, patient motion, and more. Today, these parameters are either manually configured, heuristically optimized, or compensated post hoc using multi-level calibration scans or corrections, which introduces further latency. Crucially, current MRI systems lack any form of predictive intelligence that could inform optimal configuration ahead of, or during scanning. /p pThe Computer Engineering (CE) section of the Quantum Computer Engineering (QCE) department is looking for a highly motivated PhD candidate who is eager to work on AI-based solutions for predictive intelligence for MRI scanning. /p pbWhat you will work on /b /p ul liDesign an efficient multi-level data acquisition, transport and synchronization digital infrastructure, focusing particularly on overall phase-coherent operation of the overall MRI appliance. /li liDevelop real-time system reconfiguration support using static and dynamic techniques, leading to rapid conversion to the most optimal configuration for any specific patient-centric scan scenario. /li liDevelop a novel self-calibrating, heterogeneous distributed platform capable of providing the necessary sensing, transport, compute and data aggregation capabilities on demand. /li liConsider how partial MRI measurements can be translated into meaningful input for predicting optimal sensor phase configurations and feedback control. /li liIdentify pathways towards the integration of domain knowledge about MRI physics into the platform design. /li liDevelop concrete solutions to address the issues related to integration in existing medical procedures. /li /ul pThe PhD position is part of the Z-MRI, a national project in collaboration with Philips Medical Systems. You will be part of a diverse and passionate research team of academic staff, PhD candidates and Postdoctoral researchers in the Computer Engineering group. /p pbJob requirements /b /p ul liCompleted a relevant MSc degree in Electrical Engineering, Computer Engineering, Computer Science or any other related field relevant to the research. /li liGood understanding of computer architecture and digital design. /li liBasic understanding of MRI algorithms is a plus. /li liThe ability to work in a team and take initiatives. /li /ul pbConditions of employment /b /p pDoctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met. /p pAs a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills. /p pThe TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged. /p /p #J-18808-Ljbffr
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