Scientific Software Engineer

Deep Origin is an early-stage startup that aims to use dynamical cellular modeling and simulation to revolutionize the discovery of drugs and the treatment of disease. In the same way that AI/ML has transformed medicine over the last decade, mechanistic models – from atomistic models of protein dynamics through biochemical network models of intracellular pathways and coarse-grained models of multi-cellular systems – have the potential to accelerate the development of precision therapeutics across a range of indications.

To help achieve this vision, we are seeking a talented scientific software developer to join our growing cellular simulation team. The role will focus on the development of key infrastructure used to perform mechanistic model fitting, simulation and analysis, with applications to novel therapeutic and biomarker predictions across a range of indications, particularly oncology. Additional work will involve scaling and automating the current strategy to support larger mechanistic model and analysis workloads.

Requirements

• Python fluency, with experience in numerical computing libraries (Scipy, Numpy, etc) 

• Shell scripting (preferably Bash)
• AWS cloud computing experience:
• EC2 - Configuring and launching  on-demand and spot instances
• Cloudshell, S3, Lambda 
• AMI and template development
• ECR and image management
• Docker image construction, management and deployment
• Git and Github experience
• Git repository management
• CICD Pipelines

Recommended:

• Multi-node distributed computing (preferably on AWS)
• Familiarity with ODE simulation and solvers
• Parameter optimization and algorithm knowledge

Nice to have:

• C/C++/Julia experience
• Systems biology knowledge, modeling standards (SBML, etc)
• Machine learning model development 
• Multi-omics data analysis and usage in models

Benefits

• Weekly highly specialized seminars on bio-machine learning and chemistry.

• Health insurance, family members too.
• Competitive salary and equity.