Principal Scientist, Oncology Bioinformatics
Esco Lifesciences Group provides enabling technologies, products and services to the life sciences and
healthcare industries, supporting academic research and scientific discoveries, clinical practice, as well
as biopharmaceutical R&D and manufacturing. Headquartered in Singapore, Esco has an extensive sales
network in over 100 countries, direct sales and service offices in over 24 countries, 8 manufacturing and
R&D hubs in the US, Europe, the UK, China, Singapore, Indonesia, and over 1500 employees worldwide.
Esco is poised to benefit from the sustained growth of the healthcare and biopharma industries in Asia
and globally. Esco has achieved market leadership in China, and globally, in multiple categories within
some of the fastest-growing segments — with China being its largest and fastest growing market. As a
Singapore-headquartered company, Esco is a nexus of East and West, bridging technologies, products
and talent across the world, with global operations spanning the US, Europe and Asia.
Physical/Mental Requirements/Work Environment
- Ability to author, read, analyze and interpret scientific data and publications.
- Ability to define problems, collect data, establish facts, and draw conclusions.
- Ability to focus.
- Ability to adapt and keep up with rapid changes in a fluid and dynamic environment as this is rapidly evolving space
The position will be on a project studying the evolution of cancer genomes during early steps in
carcinogenesis, with the long-term aim to develop personalized peptide therapeutics.
- Apply existing analytic pipelines and devise new algorithms to explore data derived from multiple DNA sequencing technologies for both short or HiFi reads (e.g. Pacbio, Nanopore,Illumina,etc) to resolve cancer genome evolution at the clonal level.
- Analyse complementary data from other technologies, ranging from single-cell RNA-seq to chromatin immunoprecipitation to chromatin accessibility (ATAC-seq), whole exome sequencing (WES), triple-quadrupole mass spectrometry (TQMS), spatial biology using a variety of novel cellular models.
- Create models to predict with machine learning to track response and thereby combat, suppress, and eliminate genome instability within the tumor microenvironment.
- Create models to predict cell fate and develop molecules to help in biomass expansion and cell differentiation.
- Identify and understand poor T Cell and related reactivity against computationally predicated neoantigens comparing the current state of the art and thereby developing better bioinformatic model to predict response and utilize in silico modeling to design peptide sequences for personalized peptide therapy with prediction capabilities of > 90%.
- Collaborate with laboratory and in vivo scientists to design, analyze and interpret experiments.
- A PhD in Computer Science, Bioinformatics or relevant field, with a strong track record of achievement exemplified by publications in development of neoantigens and required expertise in computational biology / bioinformatics.
- Proven track record of delivering high quality bioinformatics software tools for use by others which may include a strong publication record, contributions to GitHub repositories, publicly available analysis tools, or relevant patent filings.
- A minimum of 5 years pharmaceutical or biotech experience in bioinformatics focused on oncology, immunology or a related field.
- Knowledge of cancer biology, cancer genomics, clinical and translational science.
- Firm understanding of the principles of clonal evolution / cell fate.
- Experience analyzing DNA sequencing data.
- Familiarity with standard methods for bioinformatic data analysis and reference datasets for gene expression, mutations, and related platforms.
- Strong working knowledge of common genome analysis toolkits like GATK and BWA, as well as standard data formats common in the genomic analysis industry like FASTQ, FASTA, BCL,
- VCF, BAM etc. Proficient in computational workflows towards the optimal identification of immunogenic neoepitopes.
- Collaborating with cross functional cGMP peptide synthesis, immunology, sequencing team.
- Familiar with predictive algorithms such as NetMHCPan is highly desired.
- Familiar with deconvolution of the large LC-MS/MS data sets in combination with bioinformatic analysis to predict peptide-HLA binding affinities.
- Working with a cross functional team of chemists and biologists.
- Experience with C#, C++, or similar software languages.
- Strong Python and/or R programming skills.
- Familiar with cloud computing for data processing and analysis.
- Proficient with standard statistical analyses.
- Strong publication record.
- Excellent written and spoken English.
- Demonstrated contributions to multi-disciplinary collaborations.
- Experience in choosing the right design of Peptide sequence based on Predictive algorithms and related methods.
- Possess adequate experience in the development of neoantigens that reached late stage clinical trials and hence appropriate experience in a clinical set-up is highly desirable.
- Proficiency with Unix-based systems and running or scripting applications from the command line.
- Ability to work with any one of the popular cloud environments (AWS, GCP, Azure), containerization technologies, common workflow languages and tools, as well as data tidying and data storage best practices.
Apply now by submitting a Cover Letter and CV to [email protected].
For other job openings in Esco Lifesciences Group within the respective geographies, kindly refer to corporate website.