About the role:

We are looking for an outstanding individual to join our Computational Biology group. You will work closely with talented biochemists, microfluidics engineers, chemists and software engineers to develop single-cell and spatial genomic assays. Our products have allowed researchers to study biology at unprecedented resolution yielding insights in diverse fields such as cancer biology, immunology, neuroscience, developmental and basic biology.

Individuals applying for this position should have a deep understanding of the theory, software implementation, and practical application of statistical modeling and numerical optimization algorithms. You have exposure to distributed processing of very large text and image datasets. You are comfortable working with existing as well as creating new custom compressed data formats. You can take an idea, quickly implement it in code, and evaluate its performance. You must be self-starters, strategic thinkers, and action driven. You thrive in a fast paced and highly collaborative, interdisciplinary environment. You can communicate your ideas well, be relied on your independent thinking and technical opinion, and get the job done.

What you will be doing:

• Select, rapidly prototype and test processing methods and quality metrics involving signal processing, pattern matching and model fitting to extract relevant information from very large multidimensional datasets
• Create robust, high throughput processing pipeline for production use by leveraging CPU/GPU processor architecture to exploit the statistical properties of the data, memory layout and shape
• Build analytical models or simulations to understand and communicate key trade-offs of system design and data quality

To be successful in this role, You will need:

• PhD, MS, or equivalent industry experience in quantitative field (e.g. computer science, physics, mathematics, electrical engineering, statistics or related engineering field)
• Strong programming ability in python and compiled languages such as C/C++ and Rust
• Ability to research existing methods from literature and libraries, adapt them to the problems at hand, and turn them into well architected code
• Experience with deploying code on GPUs using various libraries and frameworks, and resorting to hand-crafted CUDA kernels if needed

Additional desirable skills to have:

• Creative problem solver who obsesses over extracting maximum performance from code while respecting imperfections inherent in real-world data
• Striking the right balance between accelerating code and maintaining theoretical guarantees
• Experience with information theory, inverse problems and multimodal image analysis