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BCforward is currently seeking highly motivated Multiscale Modeling Research Contractor in South San Francisco, CA 94080.Job Title: Multiscale Modeling Research Contractor Location: South San Francisco, CA 94080 Expected Duration: 5 months contract with possibility of extension Shift: Monday through Friday We are looking for a research contractor who will learn and apply mathematical modeling in our quest to find insights on disease mechanism by investigating biological processes at different scales that interact to determine disease phenotype transitions. The contractor will ideally have extensive experience in creating, calibrating and validating computational platforms for in silica experimentation. Familiarity with frequently used methods for comparing in silica simulation results to data extracted ex vivo is desirable. We are looking for somebody who would have experience in participating in translational research in direct collaboration between experimental and computational teams. Essential Functions Uses mathematical modelling techniques to develop spatiotemporal models of cells, tissues, and extracellular matrix to gain insights on disease mechanism Highlight key uncertainties associated with the existing data/modelling and collaborates with other team members to design additional studies that will provide necessary data to calibrate the model and test model predictions Will be a key member of cross-disciplinary discovery project teams Perform literature review in collaboration with colleagues and scientists Create and maintain documentation on progress (requirements, solutions including the codes/algorithms, and presentations) Creation of a pipeline that can utilize experimental data to calibrate model parameters, provide visualizations of model simulations and provide quantitative analysis of model simulations Provide mentoring and tutorials to make the model pipeline accessible to others post-publication Required skills/experiences Ph.D. or postdoc in mathematics or physics required Background in partial differential equations, mathematical physics, or numerical analysis and computation Experience in model selection, parameter calibration, and model validation The candidate must be published in a peer-reviewed academic journal, preferably within the field of computational biology or related subjects Knowledge of numerical modeling of solids and structures using software such as MATLAB and experience with programming languages such as Python or C Experience with open-source FEM packages (e.g. freeFEM) is desirable Prior experience working with high-performance computing clusters is highly desirable. Ability to work remotely on a cluster via tools like VS, VSCode, or command-line interaction (e.g. Bash or other command-line software) Ability to securely manage files remotely on a high-performance computing cluster using tools like Cyberduck or FileZilla Familiarity with fundamentals of biology at the undergraduate level or above Ability to develop and characterize analytic tools for quantification of simulation results (e.g. defining and measuring system-specific metrics or features) Proficiency in basic statistical methods is require, preferably using standardized tools like those used in R, MATLAB, or python Proficiency in transfer of various data between platforms and basic data curation via standard spreadsheet software (e.g. spreadsheets or MATLAB) Familiarity with local and global sensitivity analysis methods would be preferable. Ability to clearly visualize simulation output and provide clear description to their relation to biology Experience with visualization software, such as ParaView, is desirable. Any other experience in using tools for drafting technical figures (e.g. InkScape, Adobe Photoshop, Adobe Illustrator, etc.) is welcome Familiarity with standardized code version control software (e.g. GitHub or CodeOcean) Familiarity with remote collaboration software, both synchronous (e.g. Zoom, Google Meets, etc.) and asynchronous (e.g. Overleaf, Kanban board software, etc.) The candidate must possess interpersonal and teamwork skills with collaborators both within and outside of their own specialization area Familiarity with tools for communicating mathematics would be desired (e.g. LaTeX, bibTeX, or other TeX-based programs) Familiarity with tools for collaborative literature review (e.g. Paperpile, Mendeley) Experience in scientific communication (talks, posters, etc.) is desirable Prior experience working in a translational environment in collaboration between two or more disciplines is highly desirable Interested candidates please send resume in Word format Please reference job code 176264 when responding to this ad.