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Basics

Name Hector Climente-Gonzalez
Label Applied Machine Learning Researcher
Summary Applied machine learning researcher with 10+ years of experience in biology. Leveraging genetics, epigenetics and genomics to tackle open questions in human health.

Education

Work

  • 2024.11 - Present

    London, UK

    Lead Data Scientist
    Novo Nordisk, Center of Excellence for Human Genetics
    Key skills: Human genetics, Sequence learning, Pipeline development
    • Developing machine learning models for SNP interpretation, drug target discovery and disease risk prediction
    • Data mining large scale datasets (UK Biobank, GTEx, GWAS Catalog)
  • 2023.03 - 2024.11

    London, UK

    Senior Data Scientist
    Novo Nordisk, Center of Excellence for Human Genetics
    Key skills: Human genetics, Sequence learning, Pipeline development
    • Developed machine learning models for SNP interpretation, drug target discovery and disease risk prediction
    • Data mined large scale datasets (UK Biobank, GTEx, GWAS Catalog)
  • 2020.05 - 2023.02

    Kyoto, Japan

    Special Postdoctoral Researcher
    RIKEN AIP
    Key skills: Deep learning, Nonlinear feature selection, Graph regularization
    • Developed novel deep learning architectures for DNA sequence learning and computer vision
    • Developed graph methods to study RNA-seq gene expression profiles in leukemia
    • Developed strategies for FDR-controlled feature selection
  • 2016.10 - 2020.04

    Paris, France

    Ph.D. student
    Institut Curie & Mines ParisTech
    Key skills: Machine learning, Human genetics, Statistical interactions, Kernel methods
    • Developed machine learning methods that leverage graphs to study the genetics of complex diseases
    • Applied methods to discover cancer and autoimmune genetic markers in GWAS (single-SNP and epistasis)
    • Authored three software packages: martini (R, in Bioconductor), and pyHSICLasso and spada (Python, in PyPI)
  • 2014.09 - 2015.05

    Barcelona, Spain

    Head of Biocomputing
    Anaxomics Biotech Ltd.
    • Developed and maintained pipelines for the statistical analysis of RNA-seq, microarray, WGS and MS-MS data
    • Managed the bioinformatics area including decision-making, intern supervision, and interdepartment coordination
  • 2013.12 - 2016.08

    Barcelona, Spain

    Research assistant
    Pompeu Fabra University
    • Conducted a large scale study of the involvement of alternative splicing in cancer
  • 2013.06 - 2013.12

    Barcelona, Spain

    Research intern
    Centre for Genomic Regulation
    • Developed a tool to massively analyze DNA-protein interfaces from structures in the Protein Data Bank
    • Co-analyzed RNA-seq and mass spectrometry data from Mycoplasma pneumoniae

Skills

Programming
Python (numpy, pandas, scikit-learn)
Deep learning (PyTorch)
R
nextflow
C++
Bash
Big Data
Accelerated computing (CUDA, HPC)
Cloud computing (Azure)
Databases (SQL)
Omics
GWAS
Epigenetics (ATAC-seq)
RNA-seq (single cell and bulk)
MS-MS proteomics
DevOps
Virtual environments (Docker, conda)
Testing
CI/CD
Open source
git
Professional Skills
Communication: Lead writer of articles and proposals, Speaker in international conferences, Conductor of tech workshops
Project management: Managed projects within and across teams, Coordinated AI-driven research project with external partner (Microsoft)
Interpersonal: Active listener, knowledge sharing, initiated study groups and coding practice improvements

Publications

Certificates

Awards