WhiteLab Genomics was founded with the belief that life-saving drugs should be accessible to all patients in need. United in our mission, we’ve become a part of Y Combinator, French Tech 2030, Future 40 by Station F, and have been recognized by The Galien Foundation (”Best Startup” category), among other institutions at the forefront of technology and biology. Today, we strive to become the leading expert in A.I. for genomic medicine, operating as the go-to partner for research & development.

Our Computational Biology Team is at the forefront of revolutionizing genomic medicine, combining computational biology methods and data science solutions for DNA and RNA therapies design and development in the pre-clinical phase. We curate datasets and conduct in depth analyses of multiples genomic data types employing statistical and machine learning based method to optimize target discovery, payload design, and vector engineering. Our team’s expertise ensures the accelerated development of genomic therapies, offering precise solutions to intricate scientific and technological challenges in the field of biotherapies.

As a Computational Biologist, you’ll play a key role in the analysis of multi-omic datasets, with a focus on single-cell analysis, to support our research efforts to accelerate R&D in genomic medicine.

Here’s How You’ll Make an Impact:

·       Participate in collaborative research projects with academic partners, biotech and/or pharma to accelerate therapeutic target identification and development

·       Provide bioinformatics data analysis and develop innovative approaches for various research and customer projects in collaboration with the Data Science and Structural Biology teams

·      Develop and implement algorithms and statistical methods for the integration, visualization, and interpretation of complex biological data

·       Evaluate, select, and develop state-of-the-art pipelines to analyze, annotate, visualize, and integrate various biological datasets, including those generated from high throughput experiments

·      Develop internal research projects to advance core scientific methodologies, focusing on the development of methods leveraging multi-modal ‘omic data to improve biomarker identification

We’re eager to meet you if you…

·       Have a recent PhD or Masters in bioinformatics, computational biology, biostatistics, or a related field

·       Have comprehensive programming skills in Python or R with experience in bioinformatics toolkits and libraries (eg. Bioconductor, scikit-learn)

·       Are proficient in the analysis of multi-omic data, including next-generation sequencing data and high-dimensional omics datasets (especially single cell)

·      Have extensive knowledge of molecular biology principles and familiarity with biological databases and resources

·       Have a solid understanding of statistical methods used in the analysis of biological data

·      Are able to communicate complex scientific topics with internal and external stakeholders and work effectively in a collaborative research environment.

Additional skills we’re interested in (preferred, but not necessary):

·       Knowledgable in machine learning, deep learning methods and tools (eg. TensorFlow, Keras)

·       Experience with biomarker/target identification approaches

·       Experience with cloud computing platforms (eg. AWS, Google Cloud) and scientific workflows (eg. Nextflow, Terra, and Airflow on cloud or HPC services)

·       Experienced in the design and implementation of containerized applications