We are currently seeking a talented and innovative Senior Scientist, Quantitative Systems Pharmacology Modeler to join our team in Concord, MA (the Boston/Cambridge area), Pleasanton, CA (the Bay Area), or working remotely. The ideal candidate will work closely with Pharma and Biotech teams to build fit-for-purpose mechanistic pharmacokinetic/pharmacodynamic (PKPD) and Quantitative systems pharmacology (QSP) models that help drive decisions in drug discovery and development. The mathematical models may describe pharmacokinetics, pharmacodynamics, signaling pathways (intra- and cell-cell signaling), disease mechanisms, and drug toxicities.
Duties and Responsibilities:
This position is responsible for, but not limited to, the following:
- Participate as representative on multiple customer and internal project teams and work with biologists and project lead to translate biological/mechanistic understanding to mathematical models
- Develop, calibrate, and analyze mathematical models
- Clearly communicate modeling results to customers with diverse background
- Write reports for the modeling work
- Perform internal review and QC of other colleagues’ modeling work
- Develop new algorithms, methodologies, protocols and test procedures that contribute to internal & external partner goals
- Participate in internal and external team discussions, and contribute to project team strategy, especially the computational strategy
- Perform literature searches and text mining to help inform model development
- Help establish visibility for Applied BioMath’s modeling expertise by presenting at external meetings and draft publications
- Participate in writing grants to develop Applied BioMath internal QSP models and modeling capacities
Qualifications, Skills and Abilities:
- PhD or equivalent in biomedical engineering, chemical engineering, pharmaceutical sciences, biophysics, applied mathematics, biology, biochemistry or related field
- Experience with PK/PD model, QSP model, differential equation based models to describe biological systems
- Expert in differential equations and coding with MATLAB or other relevant languages
- Deep understanding and ability to independently implement standard model analyses (Monte Carlo simulation, sensitivity analysis, parameter optimization)
- Basic understanding of pharmacokinetics and pharmacodynamics for small and large molecules and drug candidates is highly desired
- Experience in building models for oncology, immunology, immuno-oncology, or neuroscience is highly desired
- Experience with population PK/PD models, statistical modeling is a plus
- Industry experience at pharmaceutical or biotech companies is a plus
- Strong interpersonal and communication skills, experience working with multidisciplinary teams and leading projects
- Experience managing workload and timeline and track record of delivering work on time
- Record of scientific achievement through peer-reviewed publications, invited oral presentations, or patents
Work Environment and Physical Requirements:
- General office environment
- May work remotely, or in either our Concord, MA or Pleasanton, CA office
Applied Biomath (www.appliedbiomath.com) is a rapidly growing, people-focused, organization that uses innovative modeling and simulation approaches to revolutionize drug invention and accelerate drug development for cutting-edge therapeutics. We have a fit-for-purpose philosophy and our projects are specifically designed to answer the unique needs of each individual client. From systems models that integrate disease pathophysiology with therapeutic mechanisms of action to population pharmacokinetic models to complex exposure-response models and model-based meta analyses, we offer a comprehensive suite of modeling and simulation services combined with strategic drug development support. Our analyses have assisted both large and small pharma and biotechs to: prioritize portfolios, identify knowledge gaps, prioritize and design experiments, predict optimal drug properties, and support clinical trials and indication/patient selection. Our results have reduced costs and accelerated timelines of drug invention. We work closely with drug program teams, scientists, program managers, protein engineers, and chemists, as well as senior managers, to best affect the outcome of drug programs in research, development, and clinical trials. We are frequently thought of as a member of the project team.
At Applied BioMath, our passion for science, technology, and helping patients is what drives our desire to revolutionize drug invention. Our team members are innovators and entrepreneurs at heart, and enjoy pioneering this paradigm shift of how drug invention is done. We love to learn, challenge ourselves and others, and create new science and opportunities. Scientists and all team members at Applied Biomath have the rare opportunity to work across therapeutic areas on treatments ranging from traditional small molecules and monoclonal antibodies to the most innovative modalities, like gene therapies, cell-based therapies, conditionally active therapeutics, antibody-drug conjugates, bispecific and multispecific antibodies, prodrugs, protein degraders, RNA-based therapies - here, you’ll see it all! As a member of our team, you’ll be on the forefront of drug discovery and development in an exciting, collaborative environment that supports your growth as a leader. We offer challenging projects and opportunities for development combined with comprehensive benefits and flexible work arrangements that help you balance your professional and personal lives. If interested in joining our team, please send your CV/resume and cover letter to firstname.lastname@example.org.
Applied BioMath is an equal opportunity employer; we take pride in maintaining a diverse and inclusive environment. We will not discriminate in recruitment, hiring, training, promotions or any other employment practices on the basis of age, color, disability, gender identity, national origin, race, religion, sexual orientation, veteran status, or any classification protected by federal, state, or local law. If you are a candidate in need of assistance or accommodation in the application process, please contact email@example.com.