Skills for Research
- The scientific method
- Bias
- Measurement and error
- Data analysis
- Types of data
- Software for data analysis
- Descriptive statistics
- Plotting data
- Introduction to inferential statistics
- Basic linear regression
- Basic logistic regression
- Advanced regression techniques
- Parametric statistical methods
- Non-parametric statistical methods
- Survival analysis
- Bayesian methods
- Machine learning
- Basic principles of machine learning
- Overview of supervised machine learning methods
- Overview of unsupervised machine learning methods
- Multiple testing
- Qualitative research
- Critical appraisal
- Epidemiology
- Clinical trials
- Imaging techniques
- Light microscopy
- Confocal microscopy
- Super-resolution microscopy
- Ramen spectroscopy
- Electron microscopy
- Ultrasound
- X-ray and computed tomography
- Magnetic resonance imaging
- Functional magnetic resonance imaging
- Magnetic resonance spectroscopy
- Single photon emision computerised tomography
- Positron emission tomography
- Magnetic resonance spectroscopy
- Magnetoencephalography
- Live imaging
- Working with nucleic acids
- PCR and variants
- Sequencing techniques
- Quantifying nucleic acids
- Storing nucleic acids
- RNA rules
- Working with protein
- Quantification of protein
- Spectrophotometry
- Western blot
- ELISA
- Localisation of protein expression within cells
- Localisation of protein expression within organisms
- Protein extraction and purification
- Identifying unknown proteins
- Identifying binding partners
- Epigenetic methods
- Genetic engineering
- Principles of genetic engineering
- CRISPR-Cas9
- Cre-lox
- Transposons
- Selective breeding
- Neuroengineering
- Model systems
- Cell culture and reprogramming
- Slice culture
- Animal models
- Computational models
- Choosing a model system
- Bioinformatics
- Investigating biological processes
- Common solutions
- Medical education
- Research ethics and governance
- Funding
- Career progression in academic medicine