SandboxAQ's AI Simulation team is seeking to amplify its ability to make inferences about biology by utilizing multimodal data ranging from various multi-omics sources to physics-based simulations to develop new drugs and materials.
Requirements
- 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
- Ability to apply advanced machine learning methods to solve complex bioinformatics problems.
- Experience with Bioinformatics tools and pipelines (e.g., BWA, GATK, Samtools, Bedtools, Seurat, Scanpy, Nextflow, Apache Airflow)
- Familiarity with 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.
Responsibilities
- Drive the development of our computational biology and bioinformatics tooling to enhance various stages in the drug discovery pipeline
- Identify relevant data sources and take responsibility for data ingestion, QC, and validation.
- Contribute to ongoing research for target ID, 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.
- 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.
Other
- PhD in a relevant field (bioinformatics, computational biology, computer science, statistics, 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.
- Speak at conferences and in pitch meetings.
- 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.
