What are the responsibilities and job description for the Systems Biology Scientist - Germany position at Deep Origin?
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 systems biologist to join our growing cellular simulation team. This role will focus on the development and validation of pathway and network models and the application of these models to novel therapeutic and biomarker predictions across a range of indications, particularly oncology. Successful candidates will have the skills and experience outlined below.
Requirements
Required skills and experience
This position is remote and can be located anywhere in the world. However, this person will work on a continental US schedule. Travel will occasionally be required to San Francisco and other locations in the US, or possibly worldwide.
Benefits
This position offers competitive salary, benefits, and equity.
To help achieve this vision, we are seeking a talented systems biologist to join our growing cellular simulation team. This role will focus on the development and validation of pathway and network models and the application of these models to novel therapeutic and biomarker predictions across a range of indications, particularly oncology. Successful candidates will have the skills and experience outlined below.
Requirements
Required skills and experience
- PhD in biological sciences, biological engineering, systems biology, computer science, physical sciences, or engineering
- Experience developing dynamical models of intracellular biochemical pathways, using either continuous or stochastic simulations such as ODEs or Gillespie-like methods
- Experience with parameter optimization tools e.g. parPE.
- Experience working with SBML.
- Knowledge of cellular biochemistry and molecular biology
- Proficiency in at least one programming language such as Julia, Python, Java, or C/C
- Experience using cloud computing services such as AWS.
- Experience with methods for high-performance and/or distributed simulation
- Experience with AI/ML
- Experience working with experimentalists and experimental data to train and validate models
- Knowledge of oncology or immunology, particularly in the application of modeling
This position is remote and can be located anywhere in the world. However, this person will work on a continental US schedule. Travel will occasionally be required to San Francisco and other locations in the US, or possibly worldwide.
Benefits
This position offers competitive salary, benefits, and equity.