skip to content
 

The Development Fund supports early career researchers (ECRs) in their professional development by providing small grants for training and other development activities. The scheme began in March 2021 and has supported the following development activities:

Recently funded projects: 

Michaelmas Term 2024

Danielle Jones - IMS-MRL    

Two week visit to MRC/UVRI & LSHTM Uganda Research Unit

Visited The Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit in Uganda

The purpose of this research visit to the MRC/UVRI and LSHTM Uganda Research Unit was to gain firsthand experience of how clinical research addressing the burden of gestational diabetes is conducted in a low-resource setting. My focus was on understanding study design and implementation, field site operations, and the regulatory frameworks governing research. This trip provided an opportunity to immerse myself in the day-to-day realities of conducting research in a diverse and dynamic setting.

 

 

Kyra Ungerleider - Clinical Neurosciences    
Working with one of the most exciting startups in women’s reproductive health at the moment, OvartiX.

Working with Dr Alex Armesilla-Diaz, VP of Research and Development at OvartiX, I will learn more about the development of high-throughput cellular screens for drug discovery in women’s health, a unique approach that OvartiX is currently working on - the experience I wouldn’t be able to have anywhere else. I will be able to apply my expertise on CRISPR screens and learn how to adapt such technology for female reproductive disorders with a significant unmet need.

 

 

 

PAST PROJECTS

2021-2022

Sexual and reproductive health training

Chanelle Scott (History and Philosophy of Science)

This course will give Chanelle strong foundational knowledge about sexual and reproductive biology and healthcare from a clinical perspective, which will broaden and complement her prior experience as a social scientist.

 

 

Training in machine learning using Stata

Dr Ulla Sovio (Obstetrics & Gynaecology)

This 2-day online machine learning course will enable Ulla to learn new skills in machine learning and to make the most of the packages available in Stata to perform various machine learning analyses.

More information

 

EMBL/EBI Summer School in Bioinformatics

Oliver Bower (Centre for Trophoblast Research)

This summer school will equip Oliver with the expertise and knowledge to begin to make use of bioinformatics in his research to pursue questions that require and use large datasets. He also plans to use this training in bioinformatics to support other projects in his lab.

 

 

Training in the biomechanics of birth

Victoria Keenan (History & Philosophy of Science)

Victoria is undertaking some training courses in the biomechanics of birth, which will give her a better understanding of how pelvic structures influence the normal physiological process of birth. She hopes to build on this knowledge to produce a related research project proposal.

 

 

2020-2021

Training in coding skills and creative non-fiction writing

Dr Lucy van de Wiel (Reproductive Sociology Research Group)

Lucy is being supported with two development activities: 1) training in Python and R; 2) training in creative non-fiction and essay writing.

 

 

Training in the statistical software Stata

Dr Francesca Gaccioli (Obstetrics & Gynaecology)

Francesca is undertaking training in the software package Stata, in order to be able to independently manage large datasets from studies involving very large cohorts of pregnant women.

More information

 

CRISPR/Cas9 training

Dr Ionel Sandovici (Obstetrics & Gynaecology)

Ionel is training in how to apply the CRISPR/Cas9 system for genome editing in mammalian cells and for generating new mouse models.

More information

 

Visiting collaboration at the University of Copenhagen

Stasa Stankovic (MRC Epidemiology Unit)

Stasa will be visiting the lab of Professor Eva Hoffmann, in order to conduct a functional analysis of findings from computational genetics work.