Imaging Scientist (MRI R&D)

Primary Objective:

Enable MRI pulse sequence development, image reconstruction, and post‑processing in the Philips MRI environment to support advanced development for oscillating gradient diffusion MRI and FLORET UTE MRI; contribute to monthly sprint deliverables.

Core Responsibilities

• Design, implement, and validate MRI pulse sequences (including diffusion, UTE, FLORET) within vendor R&D tooling/environment (Philips).
• Develop and optimize reconstruction pipelines (k‑space handling, non‑Cartesian recon, SNR/artefact mitigation, parallel imaging, compressed sensing, iterative recon).
• Build post‑processing algorithms for quantitative metrics, maps, and QA/QC.
• Run phantom and in‑vivo experiments; define protocols, acquisition parameters, and acceptance criteria; analyze results and iterate.
• Produce technical documentation (methods, parameters, validation reports) per sprint plan; support risk, test, and requirement documents.
• Collaborate with clinical/academic partners; support data governance and research contract deliverables as needed.

Must‑Have Skills & Experience

• 5–8 years in MR physics / MRI engineering / computational imaging with demonstrated work on diffusion MRI and UTE/FLORET or comparable advanced sequences.
• Hands‑on experience with vendor MRI R&D environments (Philips preferred) for sequence prototyping and deployment.
• Strong in signal/image processing and numerical optimization.
• Programming: Python (NumPy/SciPy), MATLAB, plus C for performance‑critical components; CUDA/OpenCL a strong plus.
• Reconstruction expertise: parallel imaging (SENSE/GRAPPA), non‑Cartesian/NUFFT, model‑based/iterative/CS, motion/eddy‑current correction.
• Familiarity with sprint/agile ways of working, writing requirements, and generating test reports.
• Understanding of MR safety, data privacy, and documentation standards (e.g., IEC concepts at a high level; study/contract governance awareness).

Nice‑to‑Have

• Experience with oscillating gradient diffusion, microstructural modeling, and quantitative diffusion biomarkers.
• Experience integrating toolchains (e.g., ISMRM raw data, BIDS, DICOM pipelines).
• Publications/patents in diffusion/UTE/recon methods.

Key Deliverables (per SOW cadence)

• Pulse sequence builds and change logs per sprint plan.
• Reconstruction code, test datasets, and validation metrics.
• Post‑processing workflows with documented parameters and outcomes.
• Technical documents: requirements, risks, test protocols/reports.