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Maarten Larmuseau

Data Scientist

Works remotely from Gent

  • 51.057496
  • 3.732703
  • Suggested rate 600 € / day
  • Experience 2-7 years
Propose a project The project will begin once you accept Maarten's quote.

This freelancer is available part-time (Evenings & weekends) but hasn't confirmed their availability in over 7 days.

Part-time, Evenings & weekends

Propose a project The project will begin once you accept Maarten's quote.

Location and workplace preferences

Gent, OV, België
Remote only
Primarily works remotely


Project length
≥ 6 months
Business sector
  • Biotech
  • Medical
  • Education & E-learning
  • Software Publishing
  • Nano-technology
+2 other


Freelancer code of conduct signed
Read the Malt code of conduct

Verified email


  • Dutch

    Native or bilingual

  • English


  • French



Skills (9)

Maarten in a few words

Ik ben al 6 jaar gepassioneerd met data, statistiek en machine learning bezig. Ik heb vooral ervaring met computer vision, bioinformatica en medische data, maar hou altijd van een uitdaging. Je kan voor mij terecht met alle moeilijke data science problemen die de nodige creativiteit vergen. Door mijn bredere kijk op data science mag je me ook altijd contacteren om eens te brainstormen over wat er mogelijk is met jullie huidige data.



Senior Data Scientist

Ghent, Belgium

October 2022 - Today (2 months)

As one of the first members of Visonar, my role as a senior data scientist covers a wide range of responsibilities. From configuring cloud instances to the development of commericial grade medical software to coaching junior data scientists. As a senior member, I am both involved in developing computer vision models and in setting up the product development roadmap. Biomedical imaging is a rapidly evolving field and therefore we are actively looking ahead to identify and anticipate new technologies that will revolutionize the field of nuclear imaging.

Universiteit Gent

Doctoral Researcher

October 2017 - October 2022 (5 years)

The aim of my PhD is to develop new machine learning algorithms to better understand what changes in DNA and RNA contribute to cancer progression. To build these models, I use a combination of clinical parameters, high-dimensional sequencing data and medical images such as MRI and pathology slides. Throughout my PhD I've had to report my findings to a broad, interdisciplinary audience consisting of computer science engineers, mathematicians, biologists and physicians. This has taught me a lot about the challenges of interdisciplinary communication.