About Us
Valo Health is a technology company that is integrating human-centric data and AI-powered technology to accelerate the creation of life-changing drugs for more patients faster. Valo was created with the belief that the drug discovery and development process can and should be faster and less expensive, with a much higher probability of success. We are using models early to fail less often, executing clinical trials to add valuation to the company, and generating fit-for-purpose data to feed back into Valo’s Opal Computational Platform™ as we reinvent drug discovery and development from the ground up.
Disease doesn’t wait, so neither can we. We are a multi-disciplinary team of experts in science, technology, and pharmaceuticals united in our mission to achieve better drugs for patients faster. Valo is committed to hiring diverse talent, prioritizing growth and development, fostering an inclusive environment, and creating opportunities to bring together a group of different experiences, backgrounds, and voices to work together. We achieve the widest-ranging impact when we leverage our broad backgrounds and perspectivestoaccelerate a new frontier in health. Valoseeks to become the catalyst for the pharmaceutical industry and drive the digital transformation of the industry.
Are you ready to join us?
About the Role
You will be part of the computational biology core in the
Translational Data Sciences
group, joining scientists, data scientists, and engineers building powerful computational tools and answering critical scientific questions about patients, diseases, and drug development. You will be on a team responsible for biostatistics, computational biology modeling, and machine learning in cardiovascular, metabolic, renal, and immune (CVMRI) domains.Successful candidates will work with a diverse set of scientists, entrepreneurs, and domain experts in ways that cut across traditional industry boundaries.
What you’ll do...
- Integrate ‘omics data from diverse public and proprietary sources into our data platform
- Ensure high quality data through bioinformatics pipelines, QC checks, data normalization, and correction for batch effects
- Perform DEG, GSEA, pathway/MOA, and network biology analyses to advance preclinical target identification, validation, and drug discovery programs
- Publication quality data visualization & impactful, cross-disciplinary communication
- Provide expertise in biological systems, statistics, and computational biology
- Contribute to the identification of novel targets and clinical biomarkers
- Be a dynamic and active team member, providing regular updates of your work and feedback regarding that of your colleagues
What you bring...
- BS+4, MS or PhD + 1 years experience in bioinformatics, computational sciences, computational biology, or related fields (e.g., genetics, molecular biology) in collaborative settings to unravel complex biological data challenges and communicate domain knowledge to non-computational stakeholders & colleagues
- Experience in modeling multi-omic (2 or more: genomic, transcriptomic, proteomic, and/or metabolomic) data with statistical/machine learning methods & biological network analyses towards understanding biological functions and disease processes
- Experience with high-dimensional omics data and their challenges, including biological, experimental, and computational sources of noise & variance, and approaches to address multi-collinearity
- Strong analytical, problem-solving, and communication skills, including facility with Rmarkdown and/or Jupyter Notebooks for communicating reproducible results
- Ability to also condense, summarize, and synthesize results into informative and actionable presentations to scientific audiences as demonstrated by original peer-reviewed publications in respected journals, oral presentations at scientific meetings.
- Experience in R and/or Python, including familiarity with code, data, and model versioning
- Experience with OMICs data processing workflows (e.g., nextflow, snakemake), evaluating QC metrics and adjusting for batch effects, and working in cloud environments (e.g., AWS)
- Undergraduate or graduate level course work in at least two of the following: Cell Biology, Microbiology, Developmental Biology, Physiology, Immunology, Genetics, Epidemiology, Evolution, Biochemistry, Organic Chemistry, History of Science
- Domain knowledge in cardiovascular disease and its co-morbidities (e.g., obesity, diabetes, and inflammation) preferred
- Experience with network biology (eg, WGNCA) approaches to a plus
- Familiarity with public data sources (eg, GEO, CMAP/LINCS, etc) a plus
More on Valo
Valo Health, LLC (“Valo”) is a technology company built to transform the drug discovery and development process using human-centric data and artificial intelligence-driven computation. As a digitally native company, Valo aims to fully integrate human-centric data across the entire drug development life cycle into a single unified architecture, thereby accelerating the discovery and development of life-changing drugs while simultaneously reducing costs, time, and failure rates. The company’s Opal Computational Platform™ is an integrated set of capabilities designed to transform data into valuable insights that may accelerate discoveries and enable Valo to advance a robust pipeline of programs across cardiovascular metabolic renal, oncology, and neurodegenerative diseases.
Founded by Flagship Pioneering and headquartered in Lexington, MA, Valo also has offices in New York, NY. To learn more, visit www.valohealth.com.
