Senior Scientist, Mathematical Modeler

Applied BioMath (www.appliedbiomath.com) is revolutionizing drug invention by helping partners accelerate best in class therapeutics into the clinic. We do this by integrating disease mechanisms, therapeutic mechanism of action, rigorous mathematics, high performance computing and systems pharmacology approaches. 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 accelerate timelines of drug invention. We are looking for skilled scientists who enjoy working in teams, are leaders, and can challenge themselves and colleagues, to join our rapidly growing company.

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.

We are currently seeking a talented and innovative Senior Scientist, Mathematical Modeler to join our team in Lincoln, MA (the Boston/Cambridge area). The ideal candidate will work closely with Pharma and Biotech teams to build fit-for-purpose mechanistic PKPD and QSP models that help drive decisions in drug development. Models may describe pharmacokinetics, pharmacodynamics, signaling pathways (intra- and cell-cell signaling), disease mechanisms (description and mechanistic), and drug toxicities.

Responsibilities:
-Participate as representative on multiple internal and customer 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 models
-Help establish visibility for ABM’s modeling expertise by presenting at external meetings and draft publications
-Write grants to develop ABM internal QSP models and modeling capacities

Qualifications:
-PhD or equivalent in PKPD model, QSP modeling, biomedical engineering, chemical engineering, pharmaceutical sciences, biophysics, applied mathematics, biology, biochemistry or related field
-Expert in differential equations and coding with MatLab or other relevant languages
-Deep understanding and ability to independently implement in standard model analysis (Monte Carlo simulation, sensitivity analysis, parameter optimization)
-Basic understanding of pharmacokinetics and pharmacodynamics for small and large molecules and drug candidates
-Experience in building models for oncology, immunology, immuno-oncology, or neuroscience is highly desired
-Experience with population PKPD models, statistical modeling is a plus
-Industry experience at pharmaceutical or biotech companies is highly preferred
-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

Email careers@appliedbiomath.com to apply.