October 2023 newsletter

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Will be going out around 13th October- please comment with any content you'd like included

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multi modal PDRA job ads https://cezanneondemand.intervieweb.it/turing/jobs/research-associatesenior-research-associate-turingroche-partnership-multimodal-data-integration-36800/en/

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https://www.datascienceforhealthequity.com/event-details/ucl-symposium-on-statistical-methods-for-health-equity

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https://amia.org/education-events/amia-2023-annual-symposium?utm_source=substack&utm_medium=email

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https://www.nahdo.org/conference/2023?utm_source=substack&utm_medium=email

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https://www.turing.ac.uk/events/tmcf-workshop-physics-informed-machine-learning?_cldee=rHdhYt1C31vLgAQSz2lIu2zRlpZ4o3J3js22HdsP2Uv3Qyx5Ys_VqWvFsyz-kvNw&recipientid=contact-4880a8c3923cec118c62002248434feb-b93024aaf18445eda94727b4d33d9c76&esid=f07e5a35-455d-ee11-8def-6045bdd1359d

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I am helping with a virtual Human Tumor Atlas Network (HTAN) Data Jamboree held December 4-7, 2023. This Jam will focus on single-cell and spatial omics approaches in cancer research. We are interested in creative approaches for analyzing or integrating these data and improving the utility and accessibility of single-cell and spatial omics data. Applications close Oct 24. Please feel free to reach out to me if you have any questions!

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For PhD students looking for summer internships. The call for internships with AI Research team at JPMorgan is open. Apply here: https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/job/210440922 Feel free to contact me for more information via email.

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https://digitalhealthaidata.com/class/how-can-ai-help-meet-the-rising-challenge-of-multiple-long-term-conditions-mltc/?wcs_timestamp=1698759000&_cldee=_00zc92dckm3qSVpqfb4D3wkUJxvtpeb1TTZ86YSdOdbkkxznuyyrTD_wBmybUCG&recipientid=contact-4880a8c3923cec118c62002248434feb-d46df1fd25fa454bbc631009190bb5f7&esid=865ac9fe-4447-ee11-be6f-6045bdfca65e

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JOB ADVERT - Please share with anyone suitable Coventry University’s Research Centre for Computational Science and Mathematical Modelling (CSMM) are actively looking for talented and passionate individuals to join our research team and contribute to cutting-edge projects that align with our centre’s research vision. Details on current job opportunities can be found at the following link: https://tinyurl.com/a6tsc9pe (additional positions at different seniority levels may be available for suitable candidates). The deadline for applications is 22nd October 2023.

The posts will support three application areas of strategic importance, in health, energy and security. These Assistant and Associate Professor roles are designed to promote interdisciplinary research in collaboration with other research centres at Coventry University. Candidates should be excellent computer scientists whose research expertise will strengthen CSM, and with relevant skills that would benefit one of the application areas. As part of our recruitment campaign, the Centre Directors are hosting a virtual open house event on Thursday 12th October 2023, 11:30 – 12:00 (UK time), to provide individuals with an opportunity to explore our wide-ranging research and meet our vibrant research community. Location: Zoom Webinar: https://coventry-ac-uk.zoom.us/j/82097346171?pwd=RUtBcmhLamhZUUo4MzkwM3ZGK1hZdz09 Passcode: ?+407375 We look forward to welcoming you to our virtual open house event on 12th October – no registration is needed. Interested applicants can also contact our Operations Team at Research.DSET@coventry.ac.uk, or the academic named on the relevant job opportunity, for an informal discussion.

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Enrol in an Online Learning Course: AI fairness on social media

⌛ Duration: 11-20 hours (self-paced) | 👩‍🎓Level: Independent User | 🔧 Some knowledge prerequisites (see below)

This course covers the fundamentals of algorithmic fairness, the most common biases in machine learning, and the importance of ethical and legal principles in AI design, training, and deployment. It explores the unique characteristics of social media data and the impact of AI on social good. The course discusses recent examples of algorithmic fairness in social media, AI fairness tools to mitigate discrimination and bias in ML models, and various methods and studies that address social biases in graph datasets and NLP methods. The goal of the course is to educate and prepare data scientists and engineers to ensure that their AI models are ethical, fair, and safe for use in human-in-the-loop applications.

The course is designed for all researchers in data mining, artificial intelligence and social science. The audiences are assumed to have basic knowledge on probability, linear algebra and machine learning. Knowledge of python is required.

Once you complete a course, you will automatically receive a certificate of completion, which we encourage you to share with your networks on LinkedIn. If you encounter any issues or would like to share any feedback, please get in touch at skills@turing.ac.uk.

This course has been commissioned as part of our open funding call for Responsible AI courses, with funding from Accenture and the Alan Turing Institute.

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turing news? https://www.turing.ac.uk/news/turing-university-network-expands-65-members?utm_source=LinkedIn&utm_medium=Text_link&utm_campaign=Turing-News_Turing-University-Network-expands

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https://rinpharma.com/

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HDRUK webinar A free webinar on CPRD's world-leading research data service, including its new Ethnicity Records recently added to the Gateway. Delivered by the Medicines and Healthcare products Regulatory Agency (MHRA), the Clinical Practice Research Datalink (CPRD) is a world-leading research resource that has been empowering researchers with data-driven insights for more than 30 years. Its new Ethnicity Records are a step closer to more inclusive public health research and clinical practice. Come along to our next Data Access and Discovery Webinar to find out more! When: Thursday 19 October 2023 Where: Online Time: 14:00 – 14:45 We’ll be joined by Eleanor Axson, Senior Researcher at CPRD-MHRA, who’ll take us on an in-depth tour of CPRD’s data service and its new Ethnicity Records. Paola Quattroni, Head of Alliance Strategy and Engagement at HDR UK, will also provide an update on the UK Health Data Research Alliance’s Diversity in Data workstream.

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For those who couldn't make it to the final coffee chat: We are building a network called AI for Precision Public Health! We are experts and enthusiasts from fields of artificial intelligence, causal inference and public health joining forces to prevent diseases in the first place and support health equity. If you share this purpose, you are more than welcome! Just drop your email here to join: bit.ly/ai4ph Feel free send me an email if you have any questions or comments: h.kucukali@qub.ac.uk

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I’m very excited to share the first line-up of speakers for the new season of the CIIG seminar series!:star-struck: Going forward, seminars will be on the first working Monday of every month at 3pm UK time, and will be hosted on Zoom only (no in-person option). On 6th November 3pm, our first speaker Ghadi al Hajj (University of Oslo) will be talking about DagSim - a powerful and flexible Python package for simulating data from a causal DAG, which, unlike similar existing packages, allows for unconstrained data types and relationships to be simulated. To see the abstracts, speaker bios, and register to attend, please click on the individual links below: Ghadi al Hajj (6th Nov): http://tinyurl.com/CIIG-GhadiAlHajj Peter Tennant (4th Dec): http://tinyurl.com/CIIG-PeterTennant Camilla Pegram (8th Jan): http://tinyurl.com/CIIG-CamillaPegram Everyone is welcome, looking forward to re-starting the series next month!:blush::star-struck:

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The First Multimodal AI Research Sprint: Beyond Vision & Language By The Alan Turing Institute Date: Wednesday 22 November 2023, 10:00 - 16:00

The Turing Interest Group on Meta-Learning for Multimodal Data, also with support by the Centre for Machine Intelligence at the University of Sheffield, present the first Multimodal AI Research Sprint at the Alan Turing Institute in London. This event aims to explore new horizons in Multimodal AI, specifically beyond the well-trodden domains of vision and language. They are assembling a select group of dedicated researchers and professionals for a collaborative effort aimed at producing a high-impact academic paper and laying the groundwork for ongoing, fruitful collaborations.

Registration closes Monday 6 November 2023.

More information and register here

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Tell us a little bit about yourself and your current research:

My research lies at the intersection of neuroscience, psychiatry and pharmacology. I am interested in the cross-diagnostic mechanisms underlying symptoms of anxiety and depression, which are very common and debilitating psychiatric disorders that are also highly heterogenous and comorbid. To better capture the heterogeneity of these patient populations, I investigate cognitive constructs such as affective processing, memory and mood and how they relate to differences in depression and anxiety symptomatology. In the hopes of improving future clinical care, the focus of my research is on better understanding how the most prescribed commonly pharmacological treatments, i.e., antidepressants, work differently (or not at all) for different people by affecting these cognitive processes. With an improved understanding of antidepressant response and the heterogeneity of outcomes I am hoping that treatments can be better targeted to those who are most likely to respond to them.

What is your planned community scholar project? Why is this of interest to you?

My community scholar project is a translational science methods club that brings together members of Turing, Roche as well as the wider academic but also clinical community to focus on how we can translate from data to science to clinic. This should foster discussion on how to deal with data, inference and the populations we study, addressing questions such as how to deal with different types of data, what inferences can be made from the methods we use and how this can capture and benefit patient populations. Ultimately my hope is to bring together researchers from academia and industry as well as perspectives from the clinic to critically evaluate and hopefully improve the way health data science can be conducted, generalized, and implemented.

Social question: What is your favourite meal- breakfast, lunch or dinner? Breakfast - it is the most important meal of the day and my reason to get out of bed in the morning (it is also the only socially acceptable meal that can consist entirely of chocolate).

Publication of the month is this paper https://www.jneurosci.org/content/early/2023/09/19/JNEUROSCI.0998-23.2023.abstract published in the journal of neuroscience led by researchers from UCL. This paper is quite exciting because it shows how our brain’s response to the world is guided by our expectations and that even in the general population it is common to perceive things that are not actually there (false percepts). This will hopefully inspire future work to improve our understanding the brain’s perceptual mechanisms, our subjective human experience and clinical populations such as those suffering from psychosis.

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https://www.imperial.ac.uk/jobs/description/NAT01526/chapman-fellow-mathematics/

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https://jobs.soton.ac.uk/Vacancy.aspx?ref=2462523BJ

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We are hiring a postdoc in Clinical AI and Health Equity with funding available until 31 Dec 2025. This is a project funded MRC: https://gtr.ukri.org/projects?ref=MR%2FX030075%2F1. https://www.ucl.ac.uk/work-at-ucl/search-ucl-jobs/details?jobId=15995&jobTitle=Inst[…]Informatics+-+Research+Fellow+in+Clinical+AI+%26+Health+Equity