Sort by
Refine Your Search
-
Employer
- University of Oxford
- UNIVERSITY OF VIENNA
- Durham University
- King's College London
- AALTO UNIVERSITY
- Queen Mary University of London
- University of Oxford;
- Queen Mary University of London;
- Heriot Watt University
- Imperial College London
- University of Liverpool
- University of London
- Aarhus University
- Liverpool School of Tropical Medicine;
- University of Cambridge;
- University of Dundee;
- University of Glasgow
- University of Lincoln
- University of Newcastle
- University of Reading;
- 10 more »
- « less
-
Field
-
Python and/or C/C++/Fortran. Strong motivation to work in an interdisciplinary environment at the interface of theoretical chemistry and quantum technologies. High level of self-motivation, commitment, and
-
the appointment. You should have experience applying machine learning methods to biological or genomic data, strong programming skills (preferably in Python and/or R), and an understanding of population genetics
-
at least one of R, Stata or Python, including publication-quality visualisation. Substantive knowledge of the Chinese political economy and of debates on state capitalism, marketisation and industrial policy
-
management, intellectual property or collaboration with industry or clinical partners. Competence in quantitative analysis using Python, R, MATLAB or equivalent software, including statistical analysis, image
-
C, Python, MATLAB, or similar programming languages. Experience in scientific writing and academic publishing Students in the final year of their master's programme are also welcome to apply, provided
-
biological field. You must possess documented experience managing spatial/scRNA transcriptomics workflows. Strong programming proficiency in R or Python is essential. Proven experience in data acquisition
-
programming methods in Python or similar languages, and evidence of working well as part of a multidisciplinary research team. Informal enquiries may be addressed to Professor Tingting Zhu (email: tingting.zhu
-
: computational linguistics / NLP cognitive science / psycholinguistics language acquisition or related fields Strong Python skills are essential, and experience working with corpus data or computational models
-
development of clinical risk prediction tools. You should be confident working with large and complex datasets, using statistical programming languages such as R, Python, Stata or SAS, and have a strong
-
experience in bioinformatics analysis of omics datasets, e.g. single-cell omics, including single-cell immune repertoire analysis as well as experience and knowledge of R and/or python programming