BIRALAB

Research opportunities and vacancies

BIRALAB recruits doctoral candidates, master's students, interns, postdoctoral researchers and research support staff for work on Raman spectroscopy combined with explainable artificial intelligence. Only positions still open for applications are shown here.

2 open positions

Research opportunities and vacancies

Doctoral candidates

Topics within the group's three application areas, with co-supervision by an international partner where appropriate.

  • Position type: PhD

    PhD position: Raman spectroscopy combined with AI for biomedical diagnostics

    Position description

    BIRALAB is recruiting a PhD student in the field of Raman spectroscopy combined with artificial intelligence for biomedical diagnostics. The candidate will develop explainable AI (XAI) models for Raman spectra, targeting clinical applications.

    Requirements

    BSc or MSc in computer science, applied mathematics, biomedical engineering or related field. Knowledge of machine learning and signal processing. Ability to read and write scientific English.

    Application deadline

    31 December 2026

    Send your application

Interns and undergraduate researchers

For third- and fourth-year undergraduates who want to try real research before committing to further study.

  • Position type: Internship

    Intern: Raman spectral data processing

    Position description

    BIRALAB is recruiting an intern to participate in processing and analyzing Raman spectral data. The candidate will work with experimental data, building preprocessing pipelines and training models.

    Requirements

    3rd-4th year student in computer science, applied mathematics or related field. Basic knowledge of Python and machine learning. Experience with NumPy, pandas is a plus.

    Application deadline

    30 September 2026

    Send your application

How to apply

Every position is handled through a single channel so that no application gets lost between personal mailboxes.

  1. Email admin@biralab.org with the position code or title in the subject line.
  2. Attach an academic CV (PDF), your transcript or relevant degree certificates, and a statement of at most one page explaining why you chose the Raman × AI direction and which problem you want to solve.
  3. If you have publications, code or a relevant final-year project, include DOI or repository links. We read source code, not only skill lists.
  4. Applications receive a reply within 10 working days. Shortlisted candidates are invited to an online interview and, if that goes well, a trial working session with real spectral data.
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If you would like to talk before applying, use the contact form and select the purpose “Research opportunities and recruitment”.

The research environment at BIRALAB

Read this section before applying. It describes what you will actually be doing day to day.

  • Healthcare and biomedical diagnostics

    Building classification models for Raman spectra of tissue and biofluids for non-invasive screening, with an explanation layer that identifies the wavenumber regions driving each conclusion. Work on human data proceeds only after ethics committee approval and on separate infrastructure.

  • Pharmaceutical quality control

    Quantifying active ingredients, checking content uniformity and screening for falsified medicines with non-destructive measurements, including through transparent packaging. The central problem is preserving accuracy when the model runs on commodity instruments rather than on a server.

  • Smart agriculture and food safety

    Detecting pesticide residues on produce surfaces and mycotoxins in grain, for inspection at warehouses and processing plants before export.

  • Photonics and instrumentation

    Designing integrated photonic components on silicon and assembling them into optical probes: waveguides, controllable phase shifters, mode converters, Raman probes. Positions on this track start from numerical simulation, then move to fabrication and measurement with partners.

What you will actually do

  • Prepare samples and record Raman spectra following a protocol that documents every acquisition condition — every measurement must be reproducible by someone else.
  • Preprocess spectra using the group's open standard: baseline correction, intensity normalisation, cosmic ray removal, smoothing.
  • Train and compress deep learning models to run on edge devices, evaluated with cross-validation grouped by sample rather than by spectrum.
  • Write the explainability component of the model and defend it under review: a conclusion must point to the wavenumber regions that support it.
  • Contribute to the group's open datasets and open-source tools, with documentation good enough for another group to reuse.

Co-supervision with international partners

BIRALAB doctoral candidates and postdoctoral researchers may be co-supervised by a researcher at an international partner institution alongside their supervisor at Vietnam National University, Hanoi. The closest such channel at present is the University of Greenwich (United Kingdom), where one of the group's core members is based.

How it works: the two supervisors agree the topic and review milestones at the outset, meet online on a regular schedule, and settle authorship and data sharing in writing in advance. A candidate may spend a short period at the partner institution if funding allows, but that is an opportunity subject to conditions, not a default commitment.

We state this plainly to avoid false expectations: the group does not guarantee overseas scholarships or exchange placements. What it does guarantee is serious supervision, real data to work with, and your name recorded correctly on publications.

Working conditions and support

  • Access to the group's Raman instruments and, by prior booking, to instruments of other groups in the Vietnam Raman-AI Network.
  • A scholarship or research allowance depending on the funded project; the exact amount is stated in each position description rather than left vague.
  • Support for open-access publication fees and conference attendance once a paper is accepted, within the project budget.
  • Participation in the annual Vietnam Raman-AI Network workshop and its hands-on sessions on the preprocessing standard.