Weekly working hours: 37

Contract type: Hold a fixed period

Fixed period: the date of completion: September 30, 2026

Welsh language: It does not apply

Changing your career and changing life

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About the role

The role holder will conduct research in using automatic learning on the science of vital physical simulation results in predicting and analyzing cell regulation in tumors.

The cells are active and can be manipulated and processed by their environment. This feedback between the environment and cells can lead to self -regulating tissues. This self -regulation is important for the correct work of biological tissues. We hope to understand (and in the end) cell arrangements in spherical balls and tumor.

The project will primarily include the development and testing of automated learning techniques based on vital physical simulation to predict the regulation of the tumor and analyze the level of its health. A successful candidate will also grow in the laboratory and a microscopic microscope will lead to these tissues to create cell regulation. This data will then be used to verify the authenticity of our modern techniques to predict cell arrangements in biological tissues, and to build on the Hague simulation technology, JP et al

Our ripe simulation code will be used to perform simulations. Knowing the Python Automated Framework is necessary (such as Tensorflow), as well as knowing the C ++ programming language. Some knowledge of Linux is desirable. You should be ready to apply your skills to biological systems, and implement them, if you do not already have a background in this field. We will provide training in laboratory technologies if you do not have previous experience in this field.

This project is presented:

• An opportunity to lead research papers
• Opportunities for the use and development of skills in the growth of cultivated tissue, which is a field of growing academic and industrial interest
• Opportunities to develop skills in the vital physical models of tissues and deep learning techniques

Main responsibilities

• To carry out the training to run a Condor simulation and in biomedic physics as required.
• To operate and analyze Condor on our high -performance computing set.
• To develop the deep learning model for engineering tissues, training and verify it.
• To document this model.
• To contribute to writing papers and give presentations (at EG Conferences and OU) as required.
• To contribute to the vital academic environment in the Faculty of Physical Sciences.
• Maintaining cell cultures, performing photography studies and analyzing these cultures.

About you

necessary:

• A doctorate degree will be considered in physics, biology, applied mathematics, computing, or closely related field (doctoral candidates who have presented or about to present their thesis)
• Experience of machine learning frameworks (such as Tensorflow)
• Knowing Python and C ++
• The ability to communicate the search results effectively
• Oral communication skills and good writing
• It can prove that it is a good team worker and is able to work under the private initiative
• Experience with vital physical simulation
• Prepare to work on biological systems and implement training in this field if necessary

desirable:

• Infinter with Linux operating system
• Experiment in microscope and / or wet biology
• The record of publications, which are reviewed by peers and/or conference requests, is suitable for the job stage

Support in your application

If you have any questions, or you need support or modifications related to your application, or the recruitment process, or the role, please contact us on 01908 541111 or email Careers@open.ac.uk Quoted from the reference number.

What is there for you?

At the Open University, we offer a set of benefits to learn about the wonderful work and its reward, as well as policies and flexible work that contributes to the balance of a wonderful work life. Get all the details of the benefits that we provide by visiting us Employee benefits page (Clicking this link will open a new window).

Flexible work

We are open to discussions about flexible work. Whether it is a job class, part -time, compact hours or other work arrangement. Please contact us to discuss what is better for you.

The following steps in the recruitment process

If the brief list is included, we expect the interviews on Friday 31 October or Monday, November 3.

Notice of the date of early closure

We may close this career advertisement earlier in the date of the closure published where a number of patients are received. Thus, we encourage early applications.

How to apply

To apply for this role, please submit the following document (document):

• Biography (this should also include the publishing list).
• The supportive statement, define how to meet the basic and desirable standards mentioned above.

You can view your application and contacts app when logging into our recruitment system. Please check the random/unwanted mail folders if you do not receive their associated email updates.

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