Director or Principal Computational Biologist
BioAI is seeking a highly motivated Computational Biologist to help pioneer and oversee the use of AI/ML in the biomedical sciences. The candidate will report directly to the CSO and President of R&D, work on data generated from secondary/tertiary analysis pipelines, and use AI/ML, probabilistic programming, and other statistical genomics approaches to analyze various large-scale omics data sets to better understand disease etiology, identify novel drug targets, and discover biomarkers for use in precision medicine.
Given the multi-disciplinary nature of the position, strong collaboration and communication skills are expected.
- Sc. or Ph.D. in Engineering, Computational Statistics, Computer Science, Biostatistics, Bioinformatics, or related field with a minimum of 2 years of related industry and/or academic experience
- Experience in machine learning, deep learning, statistical methodology, predictive modeling and algorithm development
- Familiar with NGS data analysis, using common bioinformatics tools (BWA, STAR, Picard, GATK etc.), and knowledge of publicly available genomics databases (i.e. ENCODE, GEO, TCGA, CCLA)
- Advanced programming skills with fluency in at least Python and/or R, with extensive experience using modern machine learning and deep learning libraries (TensorFlow, PyTorch, Edward, sklearn, caret, etc.)
- Proven ability to design and code production grade machine AI/ML applications, along with a strong ability to visualize ‘big data’
- Ability to work on high-performance computing system and manage cloud computing environments (e.g. AWS) with experience working with GPUs
- Strong communication and presentation skills with the ability to translate and communicate results to individuals of diverse backgrounds
- D. with postdoctoral training in Engineering, Computational Statistics, Computer Science, Biostatistics, Bioinformatics, or another related field with a minimum of 5 years of related industry and/or academic experience
- Minimum of 2 years of industry and/or academic research laboratory management experience
- Understanding of modern genomics analysis including RNA-seq, single cell RNA-seq, DNA methylation, variant analysis, etc.
- Development and application of digital pathology and natural language processing algorithms
- Working knowledge of biology (oncology, immunology, autoimmunity, etc.) and target identification
- Up-to-date knowledge of the fast-moving AI/ML literature