February 2023 newsletter

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Will be going out around the February 13th, please comment with any content you'd like included

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https://twitter.com/AndrewHolding/status/1613882900906213376

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Earlham Institute are recruiting for a Head of Data Science. Reporting to the Director of the EI, they are looking for a research leader who is passionate about Data Science and Machine Learning as a research field alongside the strategic management of complex datasets, software, and hardware infrastructure. https://www.earlham.ac.uk/vacancy/head-data-science

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https://www.lifeatspotify.com/jobs/summer-internship-research-scientist-experience-mission-content-platform-emea

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Online Royal Society conference on Machine learning and AI in biological science, drug discovery and medicine - 1 March 2023 @09:00-17:00: https://royalsociety.org/science-events-and-lectures/2023/03/ai-ml-in-biology-tof/

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:rotating_light: Following a short winter break, the RSF open invitation seminars are back! :rotating_light: This session should be of interest to your research groups :raised_hands: Organised by the AI for multiple long-term conditions: Research Support Facility (RSF), we'll be joined by Prof Jennifer Quint (Professor of Respiratory Epidemiology, Imperial College London) to look at the value & importance of routinely collected electronic healthcare record data, and how it's increasingly being used in clinical practice and national decision-making. :loudspeaker: Tuesday 14 February, 13:30-14:30 (UK) with Prof Jennifer Quint on ‘Using routinely collected electronic healthcare record data to study respiratory disease’. Registration is now open for the session – we hope to see you there! https://www.turing.ac.uk/events/rsf-seminar-series-using-routinely-collected-electronic-healthcare-record-data-study

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apart from our paper (see above!) our other publication of the month is...

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SM paper

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https://twitter.com/wellcometrust/status/1618195184453578754?t=WP-vADPbShtTW7or3-p5qQ&s=19

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https://www.oxfordml.school/

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https://www.turing.ac.uk/events/rsf-seminar-series-using-routinely-collected-electronic-healthcare-record-data-study

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Dear colleagues,

We are delighted to share with you the details of the next Turing Data Study Group which will be held at Newcastle University from 13 March - 24 March 2023.

Data Study Groups are intensive five-day collaborative, sprint-style research activities which bring together organisations from industry, government, and the third sector, with talented multi-disciplinary researchers from academia. Organisations act as Challenge Owners, providing real-world problems to be tackled by researchers.

The events provide a fantastic opportunity for early career researchers to rapidly develop their data science skills using real-world data. The event also offers participants the chance to forge new networks for future research projects and build links within The Alan Turing Institute and industry. We encourage PhDs, postdocs, and other early career researchers to apply.

Deadline to apply: Friday 17 February 2023 at Midday.

Challenges

The challenges put forward are: • AkzoNobel - Generative AI for Biofilm Analysis • Leeds Institute for Data Analytics - Detecting and Locating Earthquakes with Machine Learning • Leeds Institute for Data Analytics - Exploring Multimorbidity and Patterns of Long-term Conditions • Leeds Institute for Data Analytics - Volcano Deformation from Space • Northern Powergrid - Title TBC. • The Rivers Trust - Exploring the limitations and opportunities of machine learning in the freshwater environment

For detailed information about the challenges please visit our website.

Applications must be submitted via the Institute's application portal. If you have not already done so, you will need to first register on the system and provide basic details to create a profile, before you can see the application form. If you have any questions regarding the application form or using the online system, contact the Data Study Group Team. Before applying, read our guidance on how to write a successful Data Study Group application.

The Data Study Group involves a commitment of up to 50 hours across five days and participants are expected to attend the full duration of the event where possible. (While DSG does involve long hours, The Alan Turing Institute is committed to supporting individual circumstances, please email the Data Study Group team to discuss any adjustments you may require).

Find out more and apply

Please share this announcement with anyone in your networks who may be interested in applying.

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https://ojs.aaai.org/index.php/AAAI/article/view/21459 publication of the month

the paper presents how conformal predictions can be used to quantify uncertainty of machine learning models for medical imaging applications. The aim is to increase transparency and fairness of "black box" deep models for personalised healthcare and precision medicine, and "conformal learning" has strong potential to facilitate that

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Genomics England: Bioinformatics Meetup Cambridge

Date: Wednesday 22 February 2023, 18:00 - 20:00

This joint event brings together our bioinformatics community with the Cambridge Genomics Group Meetup.

Several people from Genomics England will be speaking at the event on Clinical Variant Ark and Cancer Decision Support System, followed by plenty of networking time.

• Ciaran Campbell - Clinical Bioinformatician • Will Mclaren - Lead Bioinformatics Engineer

This will be an excellent networking opportunity to meet colleagues from across academia, industry and the tech sector in the Cambridge area. Come and join a diverse group of professionals and students for a drink while mingling with other fellow scientists at one of the hottest locations to do science on Earth!

More information and register here

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Scottish AI Summit

Tuesday 28 March 2023 - Wednesday 29 March 2023

The Scottish AI Summit is an annual conference showcasing Trustworthy, Ethical, and Inclusive AI from Scotland and beyond. The conference's collaborative agenda combines keynotes, discussion panels, workshops and demonstrations. The emphasis in on delegates getting involved in the conversations around trustworthy, ethical and inclusive AI.

More information and register here

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Health Equity: Statistical Methods for Health Equity Webinar

Date: Thursday 16 February 16:00 - 17:00

The Statistical Methods for Health Equity Series is a monthly online series co-hosted by the Data Science for Health Equity community, the Alan Turing Institute Health Equity Interest Group, and the Department of Statistical Science at University College London.

For our first talk of 2023, we are delighted to welcome Dr Honghan Wu from UCL.

Dr Honghan Wu is an associate professor at Institute of Health Informatics, UCL. He is a Turing Fellow of The Alan Turing Institute. Dr Wu holds a PhD in Computing Science. His current research focuses on machine learning, natural language processing, knowledge graph and their applications in medicine. He co-leads Edinburgh Clinical NLP group.

Register here

More information about the Health Equity Interest Group here

Request sign-up here

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https://www.m2lschool.org/

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https://www.birmingham.ac.uk/research/data-science/health-data-training/health-data-immersion-week-real-world-data.aspx

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https://www.swansea.ac.uk/jobs-at-swansea/current-vacancies/details/?nPostingId=131078&nPostingTargetId=159657&id=QHUFK026203F3VBQB7VLO8NXD&LG=UK&mask=suext

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https://www.datascienceforhealthequity.com/post/challenges-to-statistical-approaches-for-health-equity?utm_campaign=b943036a-b5a9-47d3-be5b-b3a955a80e94&utm_source=so&utm_medium=mail&cid=ab33f668-3358-4a95-9cce-5fa0d5b07d32 and https://www.datascienceforhealthequity.com/post/challenges-to-statistical-approaches-for-fairness-in-genomics?utm_campaign=b943036a-b5a9-47d3-be5b-b3a955a80e94&utm_source=so&utm_medium=mail&cid=ab33f668-3358-4a95-9cce-5fa0d5b07d32

catchup on workshops- chris harbron in one and touches on missing data