newsletter august 2022

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will be going out around 9th August- please comment with any content you'd like included

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Manchester Digital Epidemiology School Date: 12-14 October 2022 Venue: Hyatt Regency Manchester, Manchester, UK The Centre for Epidemiology Versus Arthritis is hosting the 4th Manchester Digital Epidemiology School. The event is an exciting three-day course where participants will learn all about how to capture and use digital health data to support high-quality epidemiological research. The programme covers opportunities, challenges and methods across a variety of data types: from electronic health records to data collected through smartphones and wearable devices. An internationally renowned and multidisciplinary faculty from the University of Manchester, plus several external faculty members, will deliver a series of in person interactive workshops. Programme at glance: Day 1: Electronic health records (EHRs) for health research Day 2: Smartphones for health research Day 3: Wearables for health research Who is this course for? The Manchester Digital Epidemiology School is for national and international clinicians with an interest in epidemiology and/or data science, allied health professionals, researchers and epidemiologists, working in the area of musculoskeletal disease. Delegates from academic, industry and other backgrounds are welcome. How much will it cost? £150 per day (includes registration, lunch, and course materials). Register here. Deadline for booking: 30 September 2022 Please, note that spaces are limited and will be granted on a first come first served basis. More information is available on our website.

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https://www.markowetzlab.org/positions.php

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https://www.qmul.ac.uk/jobs/vacancies/items/7251.html Ginestra's postdoc

We invite applications for the position of PDRA in the School of Mathematical. The successful applicant will work in close collaboration with Prof Ginestra Bianconi (Queen Mary) and Dr Ruben Sanchez-Garcia (University of Southampton) on the project “Using network science to quantify the geometry of “missingness”, funded by The Alan Turing Institute. This project will combine methods of network science, and applied topology with information theory to develop a data driven mathematical and computational platform to extract and analyse the geometrical organization of “missingness” in complex, heterogeneous datasets. The datasets that we will consider include the Roche clinico-genomic dataset available through the Roche-Turing ‘North-Star’ partnership as well as synthetic datasets.

You will have, or be about to obtain, a PhD degree in mathematics, physics or computer science or an equivalent level of professional qualifications and experience. You should have research experience in writing high quality research papers in a field closely related to one or more of the following subjects: network science, data science, applied topology. Computational language required: Python or R. Knowledge of MATLAB and experience in handling large complex datasets preferable. An interest to work on bio-medical data is essential.

Information and application here

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https://twitter.com/Maxi_Macki/status/1549322227472076800 call for adding genomic tools?

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Opportunity for postdocs (and above) to gain (paid) experience working on projects with industry. Become a DSG PI. New positions will be posted in the next few months - hear about them 1st! :loudspeaker: To register your interest, sign up at turing.ac.uk/DSGPI Acquire further project management skills Fine tune your ability to convert commercial ideas into research projects, and vice versa Fine tune your ability to generate multiple research projects from loosely defined questions Learn about research areas of interest to you that may be relevant for the challenge at hand, but that you have not yet had the chance to explore Find out how research areas of interest to you can actually be used to generate real world impact For more detailed information, see https://www.turing.ac.uk/collaborate-turing/data-study-groups/get-involved-pi#resources

(say that partnership started in a DSG)

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https://eoscfuture-grants.eu/provider/research-data-alliance/rda-open-call-rda-eosc-future-domain-ambassadors-2

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https://markowetzlab.org/positions.php

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https://www.imperial.ac.uk/data-science/education/summer-and-winter-schools/artificial-intelligence-and-data-science-for-healthcare-innovation/?_cldee=C5jPHq61Fq86n0b0YJArWlgh9DSx1JQVJDAhXn83xcIpYShcWpmMDeLcFtsSaByG&recipientid=contact-4880a8c3923cec118c62002248434feb-2cdeef5ac36e49108cb74b33295cd3b0&esid=9802c12a-cb09-ed11-82e5-000d3ad586f3 summer school

his online summer school is designed for undergraduate students with non-technical coding backgrounds, including those studying medicine, with an interest in enhancing their skills to work in the healthcare industry.

Students will be introduced to the concept of data science and AI, hear from industry experts on these applications and work in teams towards a COVID related project. Students will:

• Develop an understanding of data science and AI’s application in healthcare. • Explain how AI is applied in medical imaging and how machine learning is used for data analysis. • Understand how medical robotics play an important role in healthcare innovation. • Present data using visualisation tools. • Understand how healthcare data can be kept safely with blockchain and how AI is used to assist electronic health records. • Explain the importance of data privacy and ethics. • Apply basic coding in Python. • Identify valuable professional skills in team building, communication and presentation and apply on team-based project. • Improve their English language.

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Turing-roche PDRA