Gavin Fay, PhD

Practice and development of skills for communicating scientific research to a diverse set of audiences. This course is for students in the sciences interested in applications of their research to management and policy, focusing on the importance of defining the `so what¿ of research and adapting messaging to specific audiences, using storytelling techniques to produce compelling presentations of scientific research.

Practice and development of skills for communicating scientific research to a diverse set of audiences. This course is for students in the sciences interested in applications of their research to management and policy, focusing on the importance of defining the `so what¿ of research and adapting messaging to specific audiences, using storytelling techniques to produce compelling presentations of scientific research.

Practice and development of skills for communicating scientific research to a diverse set of audiences. This course is for students in the sciences interested in applications of their research to management and policy, focusing on the importance of defining the `so what¿ of research and adapting messaging to specific audiences, using storytelling techniques to produce compelling presentations of scientific research.

Generalized linear models, inference of parameters in non-linear models, and Bayesian statistics. The course is designed for advanced graduate students in ecology and fisheries who want to study statistical theories in GLM and parameter inference, to infer parameters using the state-of -the art language (ADMB, BUG, R), and to develop his/her own models. Most models used in ecology and fisheries management are non-linear, and often many parameters are involved. The existing models/toolbox software are useful in research and practical management, but researchers often have their own unique problem, which those existing models cannot be used for.

Generalized linear models, inference of parameters in non-linear models, and Bayesian statistics. The course is designed for advanced graduate students in ecology and fisheries who want to study statistical theories in GLM and parameter inference, to infer parameters using the state-of -the art language (ADMB, BUG, R), and to develop his/her own models. Most models used in ecology and fisheries management are non-linear, and often many parameters are involved. The existing models/toolbox software are useful in research and practical management, but researchers often have their own unique problem, which those existing models cannot be used for.

Generalized linear models, inference of parameters in non-linear models, and Bayesian statistics. The course is designed for advanced graduate students in ecology and fisheries who want to study statistical theories in GLM and parameter inference, to infer parameters using the state-of -the art language (ADMB, BUG, R), and to develop his/her own models. Most models used in ecology and fisheries management are non-linear, and often many parameters are involved. The existing models/toolbox software are useful in research and practical management, but researchers often have their own unique problem, which those existing models cannot be used for.

Generalized linear models, inference of parameters in non-linear models, and Bayesian statistics. The course is designed for advanced graduate students in ecology and fisheries who want to study statistical theories in GLM and parameter inference, to infer parameters using the state-of -the art language (ADMB, BUG, R), and to develop his/her own models. Most models used in ecology and fisheries management are non-linear, and often many parameters are involved. The existing models/toolbox software are useful in research and practical management, but researchers often have their own unique problem, which those existing models cannot be used for.

Thesis research on an experimental or theoretical project in Marine Science or Technology under a faculty advisor.

Investigations of a fundamental and/or applied nature representing an original contribution to the scholarly research literature of the field. PhD dissertations are often published in refereed journals or presented at major conferences. A written dissertation must be completed in accordance with the rules of the Graduate School and the School for Marine Science and Technology. Admission to the course is based on successful completion of the PhD comprehensive examination and submission of a formal proposal endorsed by the student's graduate committee and submitted to the SMAST Graduate Program Director.