For recruiters & hiring managers · available early 2027

Hiring? The short version.

Role fit, logistics, and the questions recruiters ask most — on one page.

For hiring managers the short version
  • Who — Sensor systems and embedded hardware engineer. Bioengineering PhD, graduating December 2026.
  • Proof — A 14-layer mixed-signal board taken to mass production in industry. An arm-cuff monitor tested in 34 surgical patients: 83% trending concordance vs. 81% for invasive pulse contour. Five peer-reviewed papers.
  • Want — Hardware, embedded, and signal-processing roles (the six role families are below).
  • Logistics — Available early 2027 · Pittsburgh, open to relocation / hybrid / remote · F-1 OPT.

Open to Work

Actively interviewing for early-2027 start dates
Graduating December 2026
Based in Pittsburgh, PA
Open to Relocation · Hybrid · Remote
Work auth F-1 OPT

What I bring

  • System ownershipsensor board → acquisition → algorithms → user-facing tool
  • Hardware depthup to 14-layer PCBs, FPGA pipelines, AFE, EMI/EMC, PDN
  • Physics-grounded algorithmsmodels tied to how the sensor actually behaves
  • Validation disciplinebench tests, automated characterization, clinical references
  • Cross-functional communicationhardware, software, data, clinicians, papers, and demos

Best-fit problems

Products where signal quality decides whether the product works: medical devices, wearables, instrumentation, industrial sensing, robotics/automation, and semiconductor test.

Start a conversation → Download full CV (PDF)
Where I fit

Strongest where the hardware meets the data.

My core is sensor hardware and embedded systems. Signal processing, ML, and validation support that core, so I can own the chain from sensor interface to validated result. Health sensing is where I proved it.

Hardware & Embedded R&DMixed-signal PCB, MCU/FPGA, control, bring-up
Sensor Systems & InstrumentationAFE, DAQ, calibration, characterization
DSP / Algorithm EngineeringFiltering, spectral methods, feature extraction
Applied ML for Time SeriesQuality scoring, estimation, interpretable models
Test & Validation AutomationPython/C#, instruments, repeatable evidence
Medical Device & Wearable R&DClinical studies, safety interlocks, physiology

FAQ

The questions recruiters ask most, answered here so a first call can go straight to the work.

When are you available to start?

I graduate in December 2026 and am available to start in early 2027. For the right role I can consider a part-time or research-collaboration engagement earlier while I wrap up.

Remote, hybrid, or on-site?

All three work. I'm based in Pittsburgh but open to relocating anywhere in the U.S. For a strong team and problem fit, I'll also consider opportunities in Canada or Europe.

What kind of team fits you best?

Cross-disciplinary R&D teams that build sensing products. The industry can vary; what matters is that hardware, embedded acquisition, algorithms, and validation are treated as one system.

Have you worked on regulated medical devices?

My clinical studies are IRB-approved and follow human-subjects research protocols. I haven't led a formal 510(k) or IDE submission, but I've worked adjacent to design controls, IEC 62304 software lifecycle, and ISO 14971 risk management, so the vocabulary is familiar.

Can you code, or just design hardware?

Both. I design electronics and write the code that runs on them; which side leads depends on the project. I have built the whole chain: custom PCB → firmware → signal processing → ML → clinical GUI. Python daily (Pandas/SciPy/PyTorch/PyQt), C/C++ for embedded, MATLAB for prototyping, Git for everything.

References?

Available on request — my PhD advisor and clinical collaborators (PIs and Co-PIs). Reach out by email and I'll share contact details.

How should I reach you?

Email is fastest: Mahdi.Jazini@pitt.edu. LinkedIn DMs work too. I reply within a day or two.

Want to talk about a role?

Email is fastest. The full CV has every date, publication, and award.