Sougata Bhunia

PhD Researcher · National Taiwan University

Sougata Bhunia

I measure semiconductor structures smaller than the light used to see them.

Doctoral researcher in optical critical dimension metrology at NTU's Precision Metrology Lab. I recover the width, height and sidewall angle of sub-wavelength nanostructures from the light they diffract, by inverting a rigorous coupled-wave model instead of imaging the feature at all, combined with physics-informed AI super-resolution imaging and a background in high-entropy nanomaterials.

Open to collaboration and 2027 internships. Education: PhD in Nanoengineering & Nanoscience, NTU (2026–2031, expected); M.Sc. Electronics Science, Jadavpur University; B.Sc. (Hons.) Physics, University of Calcutta.

Position

PhD researcher, NTU

Lab

Precision Metrology Lab

Advisor

Prof. Liang-Chia Chen

Started / expected

Feb 2026 → 2031

Introduction

Overview

As transistors move to Gate-All-Around and 3D NAND, the tools that verify them must resolve structures far smaller than the light used to see them. I close that gap at National Taiwan University's Precision Metrology Lab, using spectroscopic scatterometry, RCWA inverse modelling and physics-informed deep networks.

I came to this from an ordinary undergraduate college in Kolkata, through a materials M.Sc. at Jadavpur University and a funded internship in Hsinchu. That route is the reason I keep a public guide for Indian students on this site.

OCD

Optical Critical Dimension

Scatterometry with RCWA inverse modelling to recover CD, height and sidewall angle, non-destructively.

AI

AI Super-Resolution

Physics-informed deep networks that reconstruct detail below the classical diffraction limit.

λ

Optical Instrumentation

Broadband interferometric setups and high-speed detection for automated wafer-level inspection.

Nm

Nanomaterials

Sol-gel synthesis and full structural, optical and thermal characterisation of oxide nanomaterials.

Toolkit

Technologies

MATLAB
Simulation
Python
AI / data
RCWA
Diffraction
NumPy
Numerics
LaTeX
Writing
Origin
Plotting
Git
Version ctl
XRD
Structure
FESEM
Imaging
EDS
Elemental
UV-Vis
Optical
TGA / DSC
Thermal
Ellipsometry
Thin film
Sol-gel
Synthesis

My work

Research Projects

Four projects, two active. Each one is written out in full (the problem, the method, and what it is worth) because that is what a reader assessing a researcher actually needs.

01

Optical Critical Dimension Metrology

Active · PhD

Semiconductor process control needs geometry, not pictures. Optical critical dimension metrology reads the geometry of a periodic structure out of the light it diffracts, so nothing has to be cleaved, coated or destroyed to be measured.

#scatterometry#RCWA#MATLAB
Read in full

The problem

Below roughly a hundred nanometres, the features that matter to a process engineer are smaller than the wavelength used to inspect them. A microscope cannot resolve them; a cross-section SEM can, but the wafer is destroyed and the answer arrives hours later. Neither is compatible with in-line control of a running process.

The information is nevertheless still present in the reflected field. A periodic grating redistributes incident light into discrete diffraction orders whose angles follow sin θₘ = sin θᵢ + mλ/Λ, and whose amplitudes depend on the exact profile of the line: its width, its height, the angle of its sidewall, the rounding at its top corner. Geometry is encoded in intensity, not in position.

How I measure it

A collimated broadband beam illuminates the grating at oblique incidence and the specular or first-order response is collected across wavelength and polarisation. That spectrum is the measurement; on its own it is not yet an answer.

The answer comes from inverting a forward model. I solve Maxwell's equations for a parameterised profile using rigorous coupled-wave analysis, expanding the periodic permittivity in Fourier harmonics and matching fields across layer boundaries, then vary critical dimension, height and sidewall angle until the simulated spectrum matches the measured one. The fitted parameters are the reported measurement.

The practical difficulty is that this inverse problem is not always well conditioned. Different profiles can produce nearly identical spectra, so much of the work is choosing wavelength ranges, incidence angles and polarisation states in which the parameters of interest are genuinely separable, and quantifying how much of the residual is real structure rather than model error.

Why it matters

A measurement that is non-destructive, fast and optical can sit inside the process loop rather than beside it. That changes what process control can be: every wafer measured instead of a sampled few, and profile drift caught while it is still correctable.

Methods & tools

  • Broadband spectroscopic scatterometry bench
  • RCWA forward solver (MATLAB)
  • Inverse fitting and regression analysis
  • Polarisation and angle-resolved acquisition

Figure: measured spectral signature of a periodic grating, with the RCWA forward-model fit overlaid.

02

Physics-Informed AI Super-Resolution

Active · PhD

Optical inspection is bounded by diffraction, not by ambition. Where a purely data-driven network will happily invent plausible detail, a network constrained by the physics of image formation can only propose detail consistent with what the instrument could have produced.

#deeplearning#python#imaging
Read in full

The problem

A diffraction-limited image is the true field convolved with the point spread function of the optics, then sampled and buried in noise. Recovering the original field is ill-posed: an infinite family of objects maps onto the same measurement, and choosing among them requires prior knowledge.

For inspection this is exactly where generic super-resolution becomes dangerous. A model trained only to make images look sharper produces confident, attractive, unfaithful edges. On a metrology tool an invented edge is worse than a blurred one, because it will be measured.

The approach

I use an encoder-decoder network with attention, but the prior is not learned from photographs. It comes from the same rigorous diffraction model used in the metrology work: simulated structures are propagated through a modelled optical path to generate physically consistent low- and high-resolution pairs, so the mapping the network learns is the inverse of a real instrument rather than of a generic blur.

The loss is likewise not purely perceptual. Reconstructions are penalised when their re-simulated optical response disagrees with the measured response, which keeps the output inside the space of fields the physics permits.

Evaluation is deliberately unglamorous: agreement of extracted geometry with the known ground truth, signal-to-noise improvement, and behaviour on structures absent from the training distribution, which is where hallucination shows up first.

Where it leads

The interesting target is not a prettier image but a tighter measurement: extracting profile parameters from a single optical capture, at a throughput no scanning technique can reach.

Methods & tools

  • PyTorch, attention U-Net architectures
  • RCWA-generated synthetic training pairs
  • Physics-consistency loss terms
  • NumPy / SciPy analysis pipeline

Figure: diffraction-limited capture beside the network reconstruction of the same field of view.

03

Lead-Free High-Entropy Perovskite Oxides

Completed · M.Sc. thesis

My M.Sc. thesis at Jadavpur University: a perovskite oxide in which five or more cations share a single crystallographic site, held in one phase by configurational entropy rather than by careful stoichiometry, and containing no lead.

#solgel#XRD#thermoelectrics
Read in full

The idea

Mixing five cations onto one lattice site should, by ordinary chemistry, give a mixture of phases. In a high-entropy oxide it does not: the configurational entropy of the disordered site lowers the free energy of the mixed phase enough to stabilise it, so the disorder itself becomes the structural principle.

That matters practically because lead is what makes many high-performing perovskite oxides work, and lead is what makes them unusable at scale. Entropy stabilisation offers a route to comparable behaviour from benign cations, with the added benefit that heavy lattice disorder scatters phonons strongly, which is desirable in a thermoelectric.

Synthesis and characterisation

Samples were prepared by a sol-gel route, chosen over solid-state mixing because atomic-scale homogeneity is the whole point: a five-cation site is only entropy-stabilised if the cations are actually mixed. Chelation, gelation, drying and calcination were varied to find the window in which a single phase forms rather than segregating.

Phase purity was established by X-ray diffraction with Rietveld refinement, which distinguishes a genuine single-phase solid solution from a convincing overlap of several patterns. Cation distribution was checked by FESEM with EDS mapping, optical bandgap extracted from UV-Vis diffuse reflectance via Tauc analysis, and thermal stability and transition behaviour measured by TGA and DSC.

What it taught me

The through-line to my current work is characterisation discipline: a claim about structure is worth exactly as much as the independent measurements that support it. That habit is what the metrology work runs on.

Methods & tools

  • Sol-gel synthesis and calcination
  • XRD with Rietveld refinement
  • FESEM with EDS mapping
  • UV-Vis diffuse reflectance, Tauc analysis
  • TGA / DSC thermal analysis

Figure: XRD pattern confirming single-phase perovskite formation; FESEM/EDS mapping for cation homogeneity.

04

Custom RCWA Solver: Chroma ATE Internship

Completed · Industry, Chroma ATE

A from-scratch, pure-Python Rigorous Coupled-Wave Analysis engine for periodic electromagnetic structures, not a wrapper around an existing solver, and validated line by line against reference implementations rather than trusted by construction.

#RCWA#python#electromagnetics#numericalvalidation
Read in full

The problem

My PhD work leans on RCWA as a forward model for optical metrology, run in MATLAB against a narrow set of grating geometries. Chroma ATE, a Taiwan-based precision test-and-measurement equipment manufacturer, needed the same physics in a more general, independently trustworthy form: a solver that could handle thin-film stacks, 1D gratings and full 2D-periodic patterned layers (vias, pillars, arbitrary cross-sections), with sloped sidewalls and dispersive, anisotropic materials, and whose correctness didn't have to be taken on faith.

Silent numerical bugs (a wrong sign convention, the wrong branch cut on a square root, an inconsistent Fourier factorization rule) are the dominant failure mode for this class of solver, not crashes. A wrong answer that runs to completion and looks plausible is far more dangerous than one that errors out.

What I built

A from-first-principles RCWA implementation in Python: numerically stable Redheffer star-product S-matrix cascading across arbitrary multilayer stacks; Toeplitz permittivity construction for patterned layers via analytic in-plane Fourier transforms; a general eigenmode solver for 1D-periodic lamellar gratings and for non-uniform 2D-periodic patterned layers; tapered and sloped sidewalls via a staircase (z-discretized) layer approximation with convergence-vs-slice-count studies; and dispersive materials from five analytic models (Sellmeier, Cauchy, Lorentz, Drude, Drude-Lorentz) or tabulated n,k data, plus anisotropic (diagonal and in-plane-coupled) permittivity tensors for both uniform and patterned layers.

Every non-trivial formula was checked against a named, line-numbered source before being trusted: the vendored S4 C++ reference solver, an independent analytic solution (Fresnel/TMM), or a published benchmark such as Moharam & Gaylord (1995). That discipline of validating before trusting a capability, not after, is documented as the project's core engineering principle.

Beyond correctness

I also treated the solver's numerical robustness as a deliverable in its own right: a documented failure contract covering every exception and warning condition, per-solve eigenvalue and mode-conditioning diagnostics, and a deterministic mode-ordering policy for near-degenerate eigenvalues, so a user can tell the difference between "the answer is right", "the answer is ill-conditioned", and "this input isn't supported yet".

Methods & tools

  • Python, NumPy: from-scratch S-matrix / eigenmode solver
  • Validation against the S4 reference implementation and analytic Fresnel/TMM
  • Literature benchmarks (Moharam & Gaylord 1995)
  • pytest-driven regression and energy-conservation checks

View the solver's source and validation suite on GitHub →

What I have done so far

Work & Education

PhD

PhD, Nanoengineering & Nanoscience

Feb 2026 to present · Taipei, Taiwan

National Taiwan University · Precision Metrology Lab

Doctoral research under Prof. Liang-Chia Chen on measuring semiconductor structures smaller than the wavelength used to inspect them, across both the optical bench and the computational side of the same problem. Expected completion 2031.

  • Building and running spectroscopic scatterometry measurements of periodic nanostructures, recovering critical dimension, height and sidewall angle by inverting an RCWA forward model rather than imaging the feature directly.
  • Developing physics-informed super-resolution networks trained on RCWA-simulated optical pairs, so reconstructions are constrained by what the instrument could actually have produced.
  • Working on the conditioning of the inverse problem: choosing wavelength, angle and polarisation regimes in which the profile parameters are genuinely separable.
  • Contributing to the lab's measurement and analysis toolchain in MATLAB and Python, and writing up results for publication.
OCD metrologyRCWADeep learningWafer inspection
Chroma ATE

Research Intern · RCWA Solver Development

13 Jul to 11 Sep 2026 · Taiwan

Chroma ATE Inc.

Two-month industry internship building sougata_solver, a from-scratch, pure-Python Rigorous Coupled-Wave Analysis (RCWA) solver for periodic electromagnetic structures, extending the same forward-model machinery behind my PhD metrology work into a validated, general-purpose engineering tool.

  • Implemented multilayer thin-film stacks, 1D-periodic lamellar gratings and general 2D-periodic patterned layers (via/pillar arrays, including elliptical and polygonal cross-sections), with numerically stable Redheffer star-product S-matrix cascading.
  • Added dispersive materials (Sellmeier, Cauchy, Lorentz, Drude, Drude-Lorentz models plus tabulated n,k data) and anisotropic permittivity tensors (diagonal and in-plane-coupled, for both uniform and patterned layers).
  • Built tapered/sloped-sidewall geometry via staircase (z-discretized) layer approximation, verified by convergence studies against slice count.
  • Validated every capability against an independent oracle (the vendored S4 C++ reference solver, analytic Fresnel/TMM solutions, or a published benchmark from Moharam & Gaylord 1995) before merging, and documented a formal numerical failure contract with eigenvalue/conditioning diagnostics.
RCWAPythonElectromagneticsNumerical validation
TEEP

Research Intern · TEEP Program

Aug to Dec 2025 · Hsinchu, Taiwan

NTHU · College of Semiconductor Research

Five months with Prof. Sourav De on semiconductor synthesis and device process flows, taking structures from growth through patterning to electrical measurement. This internship led directly to my PhD position at NTU.

  • Ran material growth and deposition steps and learned how process parameters propagate into device behaviour rather than treating them as recipe settings.
  • Followed devices end to end through patterning and integration, which is where the gap between a clean process flow on paper and a working device becomes obvious.
  • Characterised finished devices electrically and correlated the results back to the process conditions that produced them.
  • Worked inside a Taiwanese semiconductor research group in English, which is the practical reason the transition to a PhD here was straightforward.
Device fabricationProcess flowElectrical testing
MSc

M.Sc., Electronics Science

2023 to 2025 · Kolkata, India

Jadavpur University · Department of Physics

CGPA 7.72/10. Thesis under Prof. K. K. Chattopadhyay on lead-free high-entropy perovskite oxide nanomaterials, with coursework spanning quantum mechanics, device physics and nanoscale characterisation.

  • Synthesised five-cation perovskite oxides by a sol-gel route, tuning chelation, gelation and calcination to find the window where a single entropy-stabilised phase forms instead of segregating.
  • Established phase purity by XRD with Rietveld refinement and cation homogeneity by FESEM with EDS mapping.
  • Extracted optical bandgaps from UV-Vis diffuse reflectance by Tauc analysis and measured thermal stability by TGA and DSC.
  • Wrote the thesis and learned the habit that carries into my current work: a structural claim is worth only as much as the independent measurements behind it.
Quantum mechanicsSemiconductor devicesNanoelectronicsOptoelectronics
IITKGP

INUP-i2i Hands-on Workshop

Feb 2025 · Kharagpur, India

IIT Kharagpur · Indian Nanoelectronics Users Programme

Ten-day national training in nanofabrication and characterisation inside IIT Kharagpur's cleanroom, one of the few routes by which an Indian M.Sc. student gets genuine hands-on time on this class of equipment.

  • Cleanroom protocol and hands-on lithography, deposition and etch steps on shared tools.
  • Characterisation sessions on the instruments themselves rather than on their output plots.
  • Built the practical familiarity that made the later TEEP internship possible.
CleanroomLithographyCharacterisation
IISc

Winter School on Micro/Nanoelectronics

Dec 2024 · Bangalore, India

IISc · Centre for Nano Science and Engineering

Twelve-day intensive school at CeNSE on device physics and fabrication technology, taught by faculty and industry engineers working on production processes.

  • Scored 93% in the Semiconductor Technology assessment.
  • Covered device physics and process integration as a connected subject rather than as separate courses.
  • First sustained exposure to how a fab actually sequences a process, which reframed how I read the literature afterwards.
Device physicsFabrication technology
BSc

B.Sc. (Hons.), Physics

2020 to 2023 · Kolkata, India

St. Paul's Cathedral Mission College · University of Calcutta

CGPA 7.5/10. A regular undergraduate college, not a famous one, which is worth stating plainly: the foundation matters more than the letterhead.

  • Core training in classical and modern physics, electromagnetism, optics, statistical mechanics and mathematical methods.
  • Laboratory electronics, where the optics coursework first pointed toward diffraction and metrology.
  • Presented original work at an inter-college science exhibition.
OpticsElectromagnetismStatistical mechanicsElectronics

Photographs

In the Lab & Field

Lab and instrument time, cleanroom workshops, talks, and the campuses this work has run between.

Written record

Publications & Theses

No journal publications yet. I began my PhD in February 2026 and my first manuscript is in preparation. What exists so far is the written record below. This section will be updated as work is submitted.

In preparation

Physics-informed super-resolution for optical critical-dimension metrology

First-author manuscript, target submission 2027 · National Taiwan University, Precision Metrology Lab

M.Sc. thesis

Lead-free high-entropy perovskite oxide nanomaterials: synthesis and characterisation

Jadavpur University, Department of Physics, 2025 · Supervisor: Prof. K. K. Chattopadhyay

B.Sc. project

Undergraduate project in applied optics and electronics

St. Paul's Cathedral Mission College, University of Calcutta, 2023 · presented at inter-college science exhibition

Recognition

Awards & Scholarships

2025

TEEP Fellowship, Ministry of Education, Taiwan

Fully funded five-month research internship at NTHU's College of Semiconductor Research, covering flight, accommodation and monthly stipend.

2025

INUP-i2i national selection, IIT Kharagpur

Selected nationally for the Indian Nanoelectronics Users Programme hands-on cleanroom workshop, MeitY-funded.

2024

93% · Semiconductor Technology assessment, IISc CeNSE

Top-band result in the assessed component of the CeNSE Winter School on Micro/Nanoelectronics, IISc Bangalore.

Verified training

Certifications

Spoken record

Talks & Posters

2025Semiconductor synthesis and device process flow: internship review presentationNTHU, Hsinchu
2025Lead-free high-entropy perovskite oxides: M.Sc. thesis defenceJadavpur University, Kolkata
2023Undergraduate project presentation, inter-college science exhibitionUniversity of Calcutta

Who can speak for me

References

PhD advisor

Prof. Liang-Chia Chen

Distinguished Professor, National Taiwan University, Taipei

Contact details on request
M.Sc. thesis supervisor

Dr. Kalyan Kumar Chattopadhyay

Professor, Department of Physics, Jadavpur University, Kolkata

Contact details on request
M.Sc. exam co-ordinator

Dr. Jayoti Das

Professor, Department of Physics, Jadavpur University, Kolkata

Contact details on request

For Indian students

Student Guide

Everything I wish someone had told me before I applied. Written for students from ordinary Indian colleges who want to do research abroad in semiconductors and materials science.

01Why a semiconductor degree matters for Indian students

India is at an inflection point. With the India Semiconductor Mission channelling public money into fabrication and packaging capacity, and companies such as Tata Electronics, Micron and CG Power building it out, demand for engineers who understand both the underlying physics and the process is growing faster than the country is producing them.

This matters to you specifically because the shortage is not at the top. There are plenty of brilliant graduates from the IITs. What the field is short of is people from ordinary colleges who took the physics seriously, learned to run instruments, and can be trusted with a process. That is a gap you can close by decision rather than by admission result.

The knowledge is also portable in a way the institution name is not. Diffraction, band structure, deposition, lithography and characterisation are the same in Taipei, Dresden and Sanand. Nobody at a bench has ever asked me where I did my B.Sc. once I could explain what I measured and why.

One caution: choose this field because the problems interest you, not because the market is warm. The training is long and the day-to-day is patient, careful work. If you do not enjoy chasing a discrepancy in a spectrum for two weeks, the salary will not carry you.

02How to write cold emails to professors

Specificity is everything. Open by naming one specific paper of theirs, in one sentence, and say what in it connected with your own work. That single sentence is what separates your email from the fifty templated ones they received the same week.

Structure it tightly. Who you are and what you have done, in two lines. The connection to their work, in two lines. What you are asking for, stated plainly: a PhD position from a specific intake, or a funded internship. Under 200 words in total, with a one-page CV attached as PDF, named properly.

Get the register right. Do not write "Respected Sir/Madam" or "kindly do the needful"; use their title and surname, write in ordinary professional English, and do not apologise for writing. Never send a mass email with visible other recipients, and never send the same text to two professors in the same group.

Then be patient and realistic. Send in batches of five or six, keep a spreadsheet, follow up exactly once after two weeks, and treat silence as information rather than rejection. My own success rate was low. It only takes one reply.

03Building a strong CV as a physics or electronics student

Your CV is a curated argument for why a professor should spend their limited time on you. It is not a complete history of your life, and everything on it that does not advance that argument is actively working against it.

The most important entry is your thesis or project work, and it should be written concretely: what you set out to measure, which technique you used, what came out. "Synthesised five-cation perovskite oxides by sol-gel and confirmed single-phase formation by XRD with Rietveld refinement" tells a reader something. "Worked on nanomaterials" tells them nothing.

List only tools you can genuinely use, because you will be asked. A short honest list of MATLAB, Python and Origin with real work behind each is far stronger than twelve logos you once saw in a workshop. The same applies to instruments: distinguish between what you have operated and what you have watched.

Typeset it in LaTeX and keep it to one page as a student. Both signal precision before a single line is read. Cut the school marks, the photograph, the declaration and the hobby section that Indian CV templates insist on; the international convention is leaner and you should follow it.

04How to find the right lab and professor

Start with the research question, not the university ranking. A mid-ranked university with the right group and a professor who supervises properly will do more for you than a famous name where you are one of thirty students and never speak to the advisor.

Find the groups by reading. Take the two or three topics you care about, search Google Scholar for the last three years, and note who keeps appearing as last author. That list is your target list, and it will look nothing like a ranking table.

Then check the things the group webpage will not tell you. How recently were their students publishing, and did those students finish? Is funding active? Does the group work on instruments you would actually get access to, or is the equipment listed because the department owns it?

Finally, write to their current students, not only to the professor. One or two will reply honestly about supervision style, working hours and whether people are treated well. That conversation is the single most useful thing I did, and it is the step most applicants skip.

05How to skip IELTS / TOEFL for research programs

This blocks more Indian students than it should. The tests are expensive, the slots are scarce, and for many research programs they were never required in the first place.

Many programs in Taiwan, South Korea, Japan and parts of continental Europe waive the English test requirement when your prior degree was taught in English, which is true for almost every Indian science graduate. NTU and NTHU both allow this route.

What you usually need instead is a medium-of-instruction letter from your examination office or registrar, on letterhead, stating that your degree was taught and examined in English. Request it early: Indian university administrations are slower than application deadlines assume, and this one sheet of paper has cost people an intake.

Always confirm the requirement against the specific department page for the specific intake, and if it is ambiguous, email the graduate admissions office and keep the reply. Do not rely on a forum post, or on this page.

06TEEP and internships, your gateway abroad

Taiwan's Taiwan Experience Education Program is, in my experience, the most accessible fully funded short-term research internship open to Indian students in semiconductors and materials science. It typically covers flight, accommodation and a monthly stipend, so it does not depend on your family's means.

Its real value is not the stipend. A funded internship puts you inside a group for months, which is long enough for a professor to know whether they want you as a doctoral student. My TEEP at NTHU's College of Semiconductor Research in 2025 led directly to my PhD position at NTU, and that is the ordinary way these things happen rather than a lucky exception.

Apply through a professor, not only through the portal. Identify the group first, write the cold email described above, and mention TEEP as the funding mechanism for a visit you have already thought through. A professor who wants you will help the application along.

Within India, the INUP-i2i workshops at the IITs and the CeNSE winter school at IISc are the closest equivalents: real cleanroom and instrument time, national selection, and credibility on a CV. I did both, and they are what made the Taiwan application credible.

07The skills that actually matter: MATLAB, Python, LaTeX, Origin

Four tools cover most of what a physics or electronics researcher does day to day, and none of them takes a course to start.

MATLAB remains the lingua franca of optical simulation and signal processing, and in metrology groups it is often what the existing code is written in. Python with NumPy and SciPy is essential for anything data-driven, and unavoidable if you go anywhere near machine learning; learn to write it as an engineer, with version control, not as a notebook you never reopen.

Origin is still the standard for scientific plotting in materials science, and being the student whose XRD and UV-Vis figures are publication-ready is a quietly large advantage. LaTeX is non-negotiable for theses and papers, and the earlier it stops being an obstacle, the earlier your writing gets attention instead of your formatting.

Learn them on your own data during your M.Sc., not the week a deadline arrives. The skill that actually matters underneath all four is being able to take a measurement, analyse it, plot it defensibly and write it up without supervision. That is what a supervisor is really buying.

08Funding: how people actually pay for this

Assume you will not be paying. Doctoral study in the sciences is normally funded, and if a program expects you to fund yourself for years, treat that as a warning rather than an opportunity.

Funding comes in three shapes. Government scholarships, such as Taiwan's MOE and NSTC schemes, which you apply for separately and early. University or departmental fellowships, which often arrive automatically with admission. And project funding from your professor's own grants, which is the most common and the least advertised, and the reason a professor who wants you can sometimes create a position.

Ask about money directly, once you are in a real conversation. The correct question is what the monthly stipend is, whether tuition is covered, and for how many years it is guaranteed. Asking this is normal and no reasonable supervisor will hold it against you.

Also budget for the gap. Flights, initial rent and the first month before a stipend arrives are real costs that fall in the worst possible window. Plan for them explicitly rather than discovering them on arrival.

09A realistic timeline, and what to do if it does not work

Work backwards from the intake, not forwards from today. For a September or February start, you want to be shortlisting groups and reading their papers around ten to twelve months out, sending the first emails eight or nine months out, and holding documents (transcripts, medium-of-instruction letter, recommendation letters, CV) ready six months out.

Recommendation letters are the step most likely to slip, because they depend on other people. Ask your thesis supervisor early, give them your CV and a short note on what you are applying for, and remind them politely twice.

Expect this to take more than one cycle, and expect most emails to go unanswered. That is not a verdict on you; established professors receive far more mail than they can answer. The only thing that behaves reliably is volume plus specificity, sustained over months.

If a cycle fails, use the year to strengthen the argument rather than to repeat it. A workshop with genuine instrument time, a paper submitted, a real skill added, and the next round of emails is materially different. That is roughly the path I took, and there was nothing exceptional about it beyond not stopping.

Get in touch

Contact

Email is the fastest way to reach me and I answer everything that isn't automated. Worth writing about: collaboration on RCWA inverse modelling or learned reconstruction, 2027 summer internships in semiconductor metrology, or a question from a student applying abroad.