cv

General Information

Name José Guilherme de Almeida
Date of Birth 17th November 1994
Languages English (proficient), Portuguese (native), Spanish (beginner)

Education

  • 2017-2022
    PhD on computational biology
    EMBL-EBI + Cambridge University, Cambridge, UK
    • Thesis: Computational analyses of blood cells: somatic evolution and morphology
  • 2015-2017
    MSc on Cell and Molecular Biology (with honours)
    Universidade de Coimbra
    • Thesis: Computational methods for the understanding of protein-based interactions
  • 2012-2015
    BSc on Biochemistry
    Universidade de Coimbra
    • Final project: Differential expression of PD-1/PD-L1 in individuals with chronic myeloid leukaemia

Research experience

  • 2017-present
    Post-doctoral fellow
    Champalimaud Centre for the Unknown
    • With Nickolas Papanikolaou
    • Research topics
      • Development of robust machine- and deep-learning methods for prostate cancer detection and segmentation in multi-parametric magnetic ressonance imaging
      • Creation of reproducible pipelines for image registration and radiomic feature extraction
  • 2017-2022
    Doctoral fellow
    EMBL-EBI
    • With Moritz Gerstung and George S. Vassiliou
    • Research topics
      • Development of machine- and deep-learning methods to detect and characterize vast collections of cells in digitalised whole blood slides in a haematological cancer context. Predictive modelling of disease genotype using machine-learning methods to uncover cytomorphological profiles
      • Statistical and Bayesian modelling of longitudinal targeted sequencing experiments to uncover the genetic and non-genetic factors driving clonal expansion. Phylogenetic and phylodynamic modelling of the lifelong trajectories of clones using single-cell colonies in healthy individuals
  • 2016-2017
    Student researcher (MSc thesis)
    CNC-UC
    • With Irina Moreira
    • Research topics
      • Development of machine-learning protocols to determine hot-spots (important residues) in the binding interfaces of proteins
      • Structural and statistical analysis of large collections of protein-protein complexes and structural characterization of complexes with no known structure

Honors and Awards

  • 2017
    EMBL PhD fellowship
  • 2017
    MSc honours for outstanding academic performance

Technical skills

  • Programming
    • Python (advanced user), R (advanced user), C (beginner)
  • Machine-learning frameworks
    • "Traditional ML" - scikit-learn, caret
    • Deep learning - torch, tensorflow
  • Computer-vision
    • scikit-image, OpenCV
  • Statistical analysis
    • Frequentist methods
    • Bayesian methods (particularly MCMC)
  • Data visualization
    • ggplot2 (R)
  • Workflow orchestration
    • Containerisation (Docker)
    • Workflow management (snakemake)

Peer-reviewed research grants

  • 2018-2021
    Deep learning in cancer drug discovery: a pipeline for the generation of new therapies
    • Fundação para Ciências e Tecnologia (role: team member)
  • 2018-2021
    Membrane proteins development of new computational approaches and its application to GPCRs
    • Fundação para Ciências e Tecnologia (role: team member)

Other activities

  • 2016-2017
    Junior Enterprise for Science and Technology (JEST)
    • Co-founder
  • 2018
    20th EMBL PhD Symposium
    • Organization, contacting speakers
  • 2019
    EBI-Sanger-Cambridge PhD Symposium (eSCAMPS) 2019
    • Organisation, website design

Teaching experience

  • 2019
    EMBL Lautenschlager Summer School
    EMBL Heidelberg
    • Teaching young graduate students about practical bioimage analysis
  • 2016
    Workshops on Introductory Programming
    Universidade de Coimbra
    • Teaching young students about programming in Python and R