-
-equilibrium conditions. The project is a UKRI/NSF collaboration with Virginia Tech, and the use of direct numerical simulation, modelling and analysis will be complemented with experimental data from
-
driving invasion. You will work closely with our partners in African countries where An. stephensi has been detected to co-develop and implement the analysis plan for their data sets on mosquito vector
-
on a part time for 18.5 hours per week for a period of 3 months to provide cover for a colleague. Please reach out to Anh Phan at anh.phan@newcastle.ac.uk for more information. Key Accountabilities
-
& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees
-
the decision analytic modelling field research field and contribute to high quality reports for funding bodies and peer-reviewed outputs. You will hold a DPhil/PhD in health economics or a related quantitative
-
the decision analytic modelling field research field and contribute to high quality reports for funding bodies and peer-reviewed outputs. You will hold a DPhil/PhD in health economics or a related quantitative
-
interpretation of platform data, stakeholder feedback, and project outcomes; maintain records and databases; and draft progress reports, technical reports, and academic publications. Contribute to the design
-
measurement in construction. The skills, qualifications and experience required to perform the role are: Hold (or be close to obtaining) a PhD in Computer Science, Civil Engineering, Data Science, Information
-
, alongside complex drug screening, efficacy and clinical phenotype information. Using these datasets, you will undertake comprehensive strategies aimed at the characterisation and therapeutic targeting
-
systems theory Excellent analytical and problem-solving skills Desirable criteria Advanced programming and data analysis skills Computational neuroscience background Behavioral data analysis skills Strong