The Opportunity
Esco Lifesciences Group is Singapores most globalized life sciences company, with annual revenues close to SGD 200M and global operations in over 42 locations and 26 direct countries across North America, Europe, Asia, Oceania.
Esco Aster Pte Ltd is an affiliate of Esco Lifesciences Group and was first incorporated in
Esco Aster is a contract research development and manufacturing organization founded and deeply rooted by scientists enabling fellow scientists to translate their bench work into commercially available products at affordable prices.
Our scientific work is in emerging and frontier biology utilizing cells as a final product or deriving products from cells which often we use cells as the factory to derive our target product.
Our first commercial breakthrough success is Esco Aster is commercially first in class being first in the world to be certified for cultivated/cell-based meat to FSSC 22000 and by a competent food regulatory body.
We are first in the region to operate an end-to-end integrated full cell line creation/immortalization or engineered cell line, cell culture process development, analytical development for stem cells and exosomes with full cGMP Capabilities from Drug Substance and small-scale fill & finish for final Cell Therapy Product.
The work we do creates a remarkable and lasting impact on our world. We offer you an opportunity to be part of this exciting journey to own your career and firsthand exposure to new emerging modalities supporting translational sciences.
Join us as we redefine BioSolutions for One World and One Health for the current and future generations to come.
Esco Aster.
One World Biosolutions for One Health.
Who were looking for
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 Scope
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.
Job Responsibilities
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.
Requirements
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.
Preferences
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 [Confidential Information].
