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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