Duties: Lead a team that is trying to redefine personalized preventive and regenerative medicine; Apply cutting-edge machine learning, data science and biostatistical techniques to detect human age-related diseases as early as possible; Use your creativity to solve challenging problems
Requirements: We're hiring a Senior Data Scientist with expertise in machine learning and predictive statistics (analytics and modeling). Because you will be working with medical and biological datasets, some background in biomedical sciences is ideal. A deep background in Bayesian methods is highly desirable, as is fluency in R.‍

Duties: Design, build, test and refine multiple large biomarker databases in collaboration with multiple ICR teams; Work with biological data analysts to access and improve large databases of health and disease biomarkers for use in predictive analytics and predictive modeling; Conduct complex bioinformatics analyses on large genomic, transcriptomic and epigenetic data from biofluids and cell lines as well as large protein, cfDNA, miRNA and epigenetic datasets; Design and build streamlined pipelines and algorithms for database querying and multiple other applications to support complex dataset analyses
Requirements: An advanced degree in Bioinformatics or Computer Sciences with a focus on database architecture, access and querying; Extensive database architecture experience (e.g. SQL, MySQL, etc); Extensive programming experience and intimate knowledge of programming languages for statistical analysis; Experience mining, analyzing and exploring genomic, epigenetic, transcriptomic (RNAseq), proteomic, metabolomic, and other -omic datasets

Duties: Oversee the analysis of large, multi-omic datasets with the goal of finding disease signatures for diagnosis and targets for drug development; Collaborate with your ICR team members to streamline and optimize novel methodologies to identify disease-causing genomic/transcriptomic variants and find actionable targets for therapeutic development; Create and test in silico human disease models to improve predictive diagnostics; Manage a team of data scientists, computational biologists and machine learning engineers in difficult but rewarding work
Requirements: A Masters or PhD and 10 years of data science/machine learning experience, with a focus on the integration of multi-omics level datasets, diagnosing disease and target discovery; A deep background in computer programming, machine learning, mathematics, probability and statistics with an emphasis on integrating and interrogating large, multi-omic datasets

Duties: Perform high-impact, high-reward rare and hard-to-diagnose disease work; Discover novel diagnostic disease signatures and uncover actionable targets for drug development; Integrate and analyze multi-omic datasets (e.g. genomic, epigenomic, transcriptomic, proteomic, metabolomic, clinomic)
Requirements: At least post-doctoral level experience analyzing -omic datasets or similar or MS degree with 5+ years experience in -omic dataset analysis; Extensive programming experience; A strong statistics background, particularly in descriptive and predictive statistics

Duties: Spearhead the integration and analyses of multi-omic datasets to discover the causes of rare and hard-to-diagnose diseases; Manage in- and out-sourced multi-omic data collection efforts; Collaborate with your ICR team members to streamline and optimize novel methodologies to identify disease-causing genomic/transcriptomic variants and find actionable targets for therapeutic development; Create and test in silico human disease models to improve predictive diagnostics
Requirements: A PhD and at least 5 years of translational bioinformatics experience, with a focus on the integration of multi-omics level datasets; A deep background in genomics, computer programming, machine learning, mathematics, probabilities and statistics, including a philosophical understanding of probability theory and Bayesian statistics; A drive to work in an individualized medicine paradigm with the translational potential to help millions of suffering people

Duties: Oversee the analysis of large, multi-omic datasets with the goal of finding disease signatures for diagnosis and targets for drug development; Collaborate with your ICR team members to streamline and optimize novel methodologies to identify disease-causing genomic/transcriptomic variants and find actionable targets for therapeutic development; Create and test in silico human disease models to improve predictive diagnostics; Manage a team of data scientists, computational biologists and machine learning engineers in difficult but rewarding work
Requirements: A Masters or PhD and 10 years of data science/machine learning experience, with a focus on the integration of multi-omics level datasets, diagnosing disease and target discovery; A deep background in computer programming, machine learning, mathematics, probability and statistics with an emphasis on integrating and interrogating large, multi-omic datasets

Duties: Perform high-impact, high-reward rare and hard-to-diagnose disease work; Discover novel diagnostic disease signatures and uncover actionable targets for drug development; Integrate and analyze multi-omic datasets (e.g. genomic, epigenomic, transcriptomic, proteomic, metabolomic, clinomic)
Requirements: At least post-doctoral level experience analyzing -omic datasets or similar OR; MS degree with 5+ years experience in -omic dataset analysis; Extensive programming experience; A strong statistics background, particularly in descriptive and predictive statistics