Job Title: Postdoctoral Research Associate in Biophysics and Machine Learning
We are seeking a highly skilled Postdoctoral Research Associate to join our team of researchers in the field of biophysics and machine learning. The successful candidate will have a strong background in physics, biology, applied mathematics or computing and experience in machine learning frameworks.
The role involves performing research into the use of machine learning informed by the results of biophysical simulations in the prediction and analysis of cell organisation in tumoroids. This will involve predicting and analysing cell organisation in tumoroids using machine learning techniques based on biophysical simulations, growing tumoroids in the laboratory and performing confocal microscopy on those tissues to establish the organisation of cells.
Key Responsibilities:
* Predict and analyse cell organisation in tumoroids using machine learning techniques based on biophysical simulations.
* Grow tumoroids in the laboratory and perform confocal microscopy on those tissues to establish the organisation of cells.
* Validate our state-of-the-art techniques to predict the arrangements of cells in biological tissues, building on the CONDOR simulation technique.
About You:
Essential qualifications include a PhD in physics, biology, applied mathematics, computing or a closely related field. Experience of machine learning frameworks (e.g. TensorFlow) is also required. In addition, knowledge of Python and C++ is essential, as well as the ability to communicate research results effectively. Familiarity with the Linux operating system and experience in microscopy and/or wet biology are desirable.
Benefits:
* Opportunity to work in a world-leading research institution.
* Access to state-of-the-art facilities and equipment.
* Support for professional development and training.