About the job
HAYA leverages AI/ML models to decipher the regulatory genome, identify disease modifying targets in the non-coding genome, develop effective drugs, and identify circulating biomarkers. We are seeking highly motivated candidates with experience on biomarker discovery and validation for chronic diseases, to reinforce the biomarker team. As an experienced and engaged Biomarker Computational Scientist, you will work in close collaboration with discovery, pre-clinical and clinical R&D teams. You will apply your scientific acumen and creativity to build View HAYATM, a top-notch platform for biomarker discovery and validation. You will drive this platform forward to identify and develop biomarker panels (including PD and CDx panels) for HAYA’s therapeutic assets.

Primary Responsibilities:

• Drive the computational analyses to discover novel biomarkers, including pharmacodynamics and predictive biomarkers. We focus on different classes of molecules (e.g. lnc RNAs, proteins) and profiling techniques.
• Design, conceptualize and develop computational procedures, and support the design of experimental and analytical procedures, based on genomics-based biomarker assays (e.g. proteomics, transcriptomics).
• Be a subject expert on evaluating computational challenges and opportunities related to the identification of biomarkers using large scale genomics technologies and assays.
• Interpret computational findings in the context of disease biology and clinical implications.
• Actively participate in internal and external scientific projects and meetings through presentations and critical evaluation of both internal results and emerging scientific literature.

Qualifications:

• Ph D or equivalent experience in Biology, Computational Biology or related field.
• Strong experience in the analysis of data for biomarker discovery and validation. The ideal candidate has an extensive understanding of different molecular profiling techniques.
• Strong expertise in genomics biomarker assays development.
• Strong knowledge with tools, and resources used for the analysis and interpretation of omics data.
• Proficiency with statistical analysis in Python or R.
• English proficiency, strong verbal and written communication skills.
• Experience with software development platforms (e.g. Gitlab) and software development procedures and best practices is a strong plus.