Band 5 Data Science Research Assistant - The Barberry
| Posting date: | 07 November 2024 |
|---|---|
| Salary: | Not specified |
| Additional salary information: | £29,970 - £36,483 per annum, pro rata |
| Hours: | Part time |
| Closing date: | 07 December 2024 |
| Location: | Birmingham, B15 2FG |
| Company: | Birmingham and Solihull Mental Health NHS Foundation Trust |
| Job type: | Contract |
| Job reference: | 6752194/436-6752194 |
Summary
A Vacancy at Birmingham and Solihull Mental Health NHS Foundation Trust.
We are recruiting a passionate and dedicated research assistant to help build and test an algorithm to identify patients with treatment resistant depression (TRD) from electronic health records. TRD affects about 1 in 3 people with major depression and occurs when 2 or more antidepressant treatments fail to improve someone’s depression symptoms. By leveraging advanced algorithms, including natural language processing (NLP), our goal is to improve the identification of this group and to offer better treatments to those who may have been missed or have yet to achieve remission.
You will be working on mood disorders research within the Mental Health Mission – an ambitious government initiative to improve mental health treatment and infrastructure. The ideal candidate will have a strong background in statistical analysis, experience in cleaning and maintaining large datasets, and an interest in mental health research. Familiarity with data science, particularly machine learning and/or NLP would be advantageous. You must also have strong interpersonal skills, the ability to work both independently and collaborate with individuals from diverse backgrounds, and a commitment to seek input from service users. We will support your career progression and provide opportunities for you to contribute to scientific publications.
• Work closely with the Research Fellow (Dr Rebekah Amos) and other collaborators to design, refine, and test an algorithm that identifies TRD patients, using electronic healthcare records and NLP.
• Conduct and support quantitative data analysis, focusing on psychometric testing and statistical techniques. Strong expertise in handling large datasets is essential.
• Facilitate workshops with individuals who have lived experience of TRD, integrating their feedback into the algorithm’s development to improve patient outcomes.
• Liaise with stakeholders across sites, ensuring smooth communication, troubleshooting issues, and contributing to future iterations of the algorithm.
• Ensure secure storage and management of participant data in compliance with Trust policies and ethical guidelines.
• Assist with the preparation of reports, presentations, and research papers for dissemination within the Trust and the broader healthcare community.
• Stay up to date with relevant research developments in data science, mental health, and machine learning, bringing new insights to the project.
• Contribute to the preparation of future research grant applications and assist with research administration tasks as needed.
Welcome to Birmingham and Solihull Mental Health NHS Foundation Trust. Our 4000 clinical and support staff help us to improve mental health wellbeing and meet the needs of the 70,000 people we serve each year. We provide a range of mental healthcare services across Birmingham and Solihull, as well as specialised services nationally. We also offer medical, nursing and psychology training and are proud of our international reputation for both research and innovation.
Our population is culturally diverse, characterised in places by high levels of deprivation which create an increasing demand for our services and a necessity for us to make sure everyone can access the help they need. We are a team of compassionate, inclusive and committed people working together to provide excellent care to support our community. If you are looking for a place to belong, where you can make a real difference to people’s lives, join our team where our warm welcome is waiting for you.
For further information about the main responsibilities please view the attached jobdescription and person specification.
We highly recommend you submit your application as soon as possible, this post may close earlier than the indicated closing date if a sufficient number of applications are received.
This advert closes on Monday 25 Nov 2024
We are recruiting a passionate and dedicated research assistant to help build and test an algorithm to identify patients with treatment resistant depression (TRD) from electronic health records. TRD affects about 1 in 3 people with major depression and occurs when 2 or more antidepressant treatments fail to improve someone’s depression symptoms. By leveraging advanced algorithms, including natural language processing (NLP), our goal is to improve the identification of this group and to offer better treatments to those who may have been missed or have yet to achieve remission.
You will be working on mood disorders research within the Mental Health Mission – an ambitious government initiative to improve mental health treatment and infrastructure. The ideal candidate will have a strong background in statistical analysis, experience in cleaning and maintaining large datasets, and an interest in mental health research. Familiarity with data science, particularly machine learning and/or NLP would be advantageous. You must also have strong interpersonal skills, the ability to work both independently and collaborate with individuals from diverse backgrounds, and a commitment to seek input from service users. We will support your career progression and provide opportunities for you to contribute to scientific publications.
• Work closely with the Research Fellow (Dr Rebekah Amos) and other collaborators to design, refine, and test an algorithm that identifies TRD patients, using electronic healthcare records and NLP.
• Conduct and support quantitative data analysis, focusing on psychometric testing and statistical techniques. Strong expertise in handling large datasets is essential.
• Facilitate workshops with individuals who have lived experience of TRD, integrating their feedback into the algorithm’s development to improve patient outcomes.
• Liaise with stakeholders across sites, ensuring smooth communication, troubleshooting issues, and contributing to future iterations of the algorithm.
• Ensure secure storage and management of participant data in compliance with Trust policies and ethical guidelines.
• Assist with the preparation of reports, presentations, and research papers for dissemination within the Trust and the broader healthcare community.
• Stay up to date with relevant research developments in data science, mental health, and machine learning, bringing new insights to the project.
• Contribute to the preparation of future research grant applications and assist with research administration tasks as needed.
Welcome to Birmingham and Solihull Mental Health NHS Foundation Trust. Our 4000 clinical and support staff help us to improve mental health wellbeing and meet the needs of the 70,000 people we serve each year. We provide a range of mental healthcare services across Birmingham and Solihull, as well as specialised services nationally. We also offer medical, nursing and psychology training and are proud of our international reputation for both research and innovation.
Our population is culturally diverse, characterised in places by high levels of deprivation which create an increasing demand for our services and a necessity for us to make sure everyone can access the help they need. We are a team of compassionate, inclusive and committed people working together to provide excellent care to support our community. If you are looking for a place to belong, where you can make a real difference to people’s lives, join our team where our warm welcome is waiting for you.
For further information about the main responsibilities please view the attached jobdescription and person specification.
We highly recommend you submit your application as soon as possible, this post may close earlier than the indicated closing date if a sufficient number of applications are received.
This advert closes on Monday 25 Nov 2024