Bioinformatics Researcher, Knowledge Graphs Researcher

Summary

Join SandboxAQ's AI Simulation team as a Bioinformatics / Knowledge Graphs Researcher. You will develop software for biomedical knowledge graphs, identify relevant data sources, and contribute to research applications. Responsibilities include implementing bioinformatics and deep learning algorithms, presenting findings to various audiences, and collaborating with external partners. This role requires a PhD in a relevant field and 1-5 years of experience in bioinformatics, computational biology, or related areas. Experience with large-scale data processing, Python toolkits, and bioinformatics tools is essential. The position offers a competitive salary, stock options, generous learning opportunities, comprehensive benefits, and a collaborative work environment.

Requirements

• PhD in a relevant field (bioinformatics, computational biology, computer science, high performance computing or similar)
• 1-5 years of relevant experience including hands-on experience in the private sector working on projects related to one of: bioinformatics, statistical genetics, computational biology, machine-learning, or knowledge graphs
• Experience processing and curating large-scale omics, clinical data, medical records, and scientific literature data
• Experienced with common python toolkits for scientific computing (e.g. pandas, numpy, scipy), machine learning (e.g. scikit-learn, pytorch), and bioinformatics (e.g. biotite, biopython)
• Experience with secondary and tertiary analysis of sequencing data related to DNA sequencing, RNA-seq, epigenomics, functional genomics, Single-cell and spatial omics, Single-cell CRISPR screens
• Experience with Bioinformatics tools and pipelines (e.g. BWA, GATK, Samtools, Bedtools, Seurat, Scanpy, Nextflow, Apache Airflow)
• Familiarity running analyses and training models on high-performance computing (GPU) environments for corporate R&D, innovation labs, or academic research
• An interest in solving scientific problems in chemistry and biology via computational and data-driven methods
• A drive to cooperate with colleagues to identify problems and communicate technical solutions in an accessible manner
• Hands-on mentality & comfortable with getting deep into the technical weeds of highly complex problems, and a track record of driving projects to completion

Responsibilities

• Create and implement software to construct and perform operations on biomedical knowledge graphs, drawing from simulated, omics, and literature data
• Identify relevant data sources and take responsibility for data ingestion, QC, and validation
• Contribute to ongoing research towards applications of the above, including for biomarker ID, patient stratification, and toxicity prediction
• Research and implement novel bioinformatics and deep learning algorithms for deciphering human genetic variants, gene regulation, gene expression, and disease pathways by using information from clinical phenotypes and medical records, multi-omics, single cell, proteomics, and genomic data
• Present to and interact with anyone who needs to understand your work, including clients, other scientists, and non-technical team members
• Write patents, journal articles, and whitepapers. Speak at conferences and in pitch meetings
• Work closely with external partners to understand their current challenges for Drug Discovery projects, identify relevant data sets, and research requirements to drive research partnerships forward
• Vastly improve drug discovery and development on a social scale. Help make better drugs, and help make the tools to do so

Preferred Qualifications

• Familiarity with cloud-based platforms (e.g. Google Cloud Platform, AWS) for data processing and storage
• Demonstrated work on building a pipeline for processing and working with “omics” datasets
• Knowledge of Genomic databases (e.g. 1000 Genomes, UK Biobank, GTEx, TCGA)
• Knowledge of biomarker ID and toxicity prediction
• Experience in clinical development
• Experience in immunology
• Excellent publication record
• Willingness to travel less than 25% to conferences, offsites, customers, and internal meetings

Benefits

• Competitive salaries
• Stock options depending on employment type
• Generous learning opportunities
• Medical/dental/vision
• Family planning/fertility
• PTO (summer and winter breaks)
• Financial wellness resources
• 401(k) plans
• Annual discretionary bonuses
• Equity