The course aims to take students with undergraduate degrees in relevant scientific disciplines in Physical sciences (e.g., Astronomy, Physics, Chemistry, Earth Sciences, Mathematics), and Biological Sciences (e.g., Zoology, Plant Sciences, genetics) and to equip them with the academic knowledge and excellent skills in managing complex interdisciplinary projects involving:
· Societal demand for multi-domain expertise to tackle the challenges posed by observing and modelling complex systems;
· The need to train postgraduate students with high levels of interdisciplinary fluency and team working skills;
· A demand for highly trained research scientists able to drive data analysis on feature-rich sets of data from diverse sources;
· The development of students’ expertise in the techniques used to study planets, from the Earth’s deepest past, the solar system planets, to exoplanets;
· The working knowledge of the structure of life, its essential physical- chemical requirements, and its impacts on planetary environments;
· Essential practical experience in running a research project in an interdisciplinary team; and,
The capacity in modern data handling techniques and an awareness of the wide range of academic and industrial applications of these skills.
Learning outcomes
By the end of the programme, students will have:
Knowledge and understanding:
K1. A knowledge of the key scientific concepts in Earth Science, Physics, Chemistry and Biology that contribute to planetary Science and Life in the Universe.
K2. A clear understanding of methods and techniques to discover and characterize planets, exoplanets, and their biospheres.
K3. The ability to critically evaluate scientific tools and methodologies for their application in Planetary Science and Life in the Universe.
K4. Demonstrated originality in tackling and solving problems and acted autonomously in the planning and implementation of research.
Skills and other attributes:
S1. Collaborative and organizational skills via projects management, including a team- based research project.
S2. The ability to communicate their work clearly, both orally and in writing.
S3. An awareness of the wide range of academic and industrial applications of being skilled at assimilating feature rich datasets to solve complex problems.
Transferrable skills training is delivered through the three group-based projects running over the year: these provide a unique opportunity for students to gain experience of leadership, collaboration, and written and oral communication.
Competency standards
Students must achieve the following standards to graduate from the course:
C1. Effective communication. The ability to produce structured scientific communication in coursework and closed-book assessment with appropriate motivation for the science, presentation of the results of science and critical analysis of science appropriate to the target audience, whether scientific peers or a non-specialist audience.
Developed in – core course, advanced courses, all project work.
C2. Interdisciplinary Scientific Reasoning. The ability to integrate concepts, methods, and evidence from multiple of the programme's contributing disciplines (astrophysics, Earth science, chemistry, biology) to construct, evaluate, and defend coherent scientific arguments.
Developed in – The core course, science communication challenge and research project.
C3. Research Design and Autonomy. The ability to independently formulate a research question, design an appropriate methodology, and execute a research plan within a defined scope, demonstrating the level of autonomy expected for entry into doctoral research or equivalent professional practice.
Developed in – research project.
C4. Critical Evaluation of Scientific Evidence. The ability to evaluate primary scientific literature and datasets with appropriate scepticism, to identify limitations in methodology, data quality, and interpretation, and to articulate the degree of uncertainty in conclusions drawn.
Developed in – all project work.
C5. Quantitative Analysis and Interpretation. The demonstration of competence in mathematical analysis and manipulation, and the interpretation of complex datasets using appropriate computational tools and statistical methods, with proper uncertainty quantification.
Developed in – core course, advanced courses, and research project.
C6. Collaboration. The ability to effectively engage in coordinated action within interdisciplinary groups to achieve the shared research objectives.
Developed by – all project work.
Continuing
Students wishing to progress to PhD study after passing the MPhil degree should reapply for admission to a PhD through the University admissions website, taking the funding and application deadlines into consideration.
Open Days
The University hosts and attends fairs and events throughout the year, in the UK and across the world. We also offer online events to help you explore your options.
Discover Cambridge: Master’s and PhD study webinars
Practical, step-by-step information about preparing a strong application for postgraduate study. Find out more on the Discover Cambridge webpage.
Virtual Postgraduate Open Days
The November Open Days focus on subject and course information. Webinar recordings are available until May.
Events for international students
Join us for Q&A webinars, funding webinars or get in touch with our regional managers. Find out more about events for international students.
For more information about all upcoming events visit our events pages.
Departments
This course is advertised in the following departments: