Bienvenue sur le profil Malt de Thomas !

Malt vous permet d'accéder aux meilleurs consultants freelances pour vos projets. Contactez Thomas pour échanger sur votre besoin ou recherchez d'autres profils sur Malt.

Thomas Minot

machine learning engineer

Peut se déplacer à Marseille, Paris, Lyon

  • 43.2954
  • 5.3631
Proposer un projet La mission ne démarrera que si vous acceptez le devis de Thomas.
Proposer un projet La mission ne démarrera que si vous acceptez le devis de Thomas.

Localisation et déplacement

Localisation
Marseille, France
Peut travailler dans vos locaux à
  • Marseille et 50km autour
  • Paris
  • Lyon

Vérifications

Influence

Langues

Catégories

Compétences (6)

Thomas en quelques mots

Having worked in computer vison and neurotech, I have both industrial (R&D / production) and lab research experience.

My skills range from delivering machine learning pipelines to implementing from scratch theoretic models found in novel research publications.

My knowledge includes a variety of languages, tools and frameworks related to general programing but also more specifically about data science, deep learning, embedded systems.

Expériences

Hemera systems

High tech

Machine learning engineer

Paris, France

février 2020 - Aujourd'hui

Developing models for time series forecasting applied to blockchain-based medium and high frequency trading
Implementing mutli-scale strategies for order execution on cryptocurrency assets
Training on public/private data from crypto exchange platforms and social media feeds/sentiment

Another Brain

High tech

Machine learning engineer

Paris, France

mai 2019 - février 2020

Developed computer vision solutions for anomaly detection in industrial factories
Implemented software solutions on assembly lines, integrated hardware and vision systems (computing unit, lighting,
camera, robot arm)
Created P.O.C. and demos for several clients on custom datasets with state-of-the-art generative stochastic models

Cortical Labs

Centres de recherche

Computer science engineer

Melbourne, Australie

octobre 2018 - novembre 2019

Conducted​ ​ multidisciplinary research on neural interfacing and biocomputing
Simulation of environments for embodied cognition based on cultures of cortical neurons
Implemented a framework for neurocomputation constructing feedback loops on biological neural networks
(Rust application communicating with MEA systems)
Built an efficient unsupervised artificial CNN for hebbian learning (custom operators using Pytorch)

Oxford University

Centres de recherche

Computational neuroscience researcher

avril 2015 - septembre 2015

Recommandations externes

Consultez les recommandations qu'a reçues Thomas

Formations