Research Fellow in Machine Learning, Deep Learning and Artificial Intelligence (Fixed term)

University of Nottingham


17 Jun 2023
Job Information

Organisation/Company
University of Nottingham
Research Field
Biological sciences » Biology
Computer science » Other
Computer science » Programming
Researcher Profile
Recognised Researcher (R2)
Country
United Kingdom
Application Deadline
12 Jul 2023 – 22:59 (UTC)
Type of Contract
Temporary
Job Status
Full-time
Hours Per Week
36.25
Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?
No

Offer Description
Veterinary Medicine & Science

Location:  Sutton Bonington 

Salary:  £33,348 to £34,314 per annum (pro-rata if applicable) depending on skills and experience. Salary progression beyond this scale is subject to performance. 

Closing Date:  Wednesday 12 July 2023 

Reference:  MED244923

We are seeking a research fellow to take a leading role in research projects related to infection and antimicrobial resistance.

The aim of this research is to understand the emergence, spread and transmission of drug-resistant pathogens in the Agri-tech/health sector (e.g. farms, environment, hospitals, community), with a potential transfer to the human population. We aim to improve diagnostic capabilities for detecting infections and antimicrobial resistance to support treatment selection and the development of novel solutions for better surveillance. This will be done through the development and implementation of big data mining and machine learning-powered solutions for monitoring and diagnostics of infection and resistance. Our analysis will also target another important aspect linked to antibiotic-resistant infections: gain a better understanding of the complex genetic repertoire, molecular interaction networks and pathways underlying resistance (i.e. the resistome) to broaden the possibility of discovery of novel therapeutic targets. To this aim, we will use artificial intelligence, bioinformatics and microbiology to identify new potential druggable targets that may render the microbe susceptible to antibiotics when blocked. Next, and utilizing other learners, we will identify drugs that can block these targets. The successful candidate will work closely with an interdisciplinary team of academics at University of Nottingham, Ningbo Campus, China and industrial partners in the UK and China and industrial partners in the UK and China. 

The Applicant must have, or be very close to completing, a PhD in machine learning, computer science, engineering, mathematics, statistics, physics, or other relevant fields. The candidate must have knowledge and experience in machine learning, deep learning and artificial intelligence techniques. Experience in heterogeneous, complex large-scale data, including sequencing, sensor, biological and imaging data would be desirable. Research experience in applying such methods in antimicrobial resistance, metagenomics, bacterial infections, food and health-related issues and expertise in cloud-based environments would be relevant. Applicant must be able to demonstrate strong programming skills in Python, Matlab, R or other equivalent. Evidence of publications in any of the listed fields. The applicant must also be able to demonstrate research ambition through timely publication of research, coupled with commitment to the research project as part of their on-going career development. 

This position is offered on a fixed term basis until 31 May 2025. Hours of work are full-time (36.25 hours), however applications are also welcome from candidates wishing to work part-time (minimum 18.13 hours per week). Please specify in your application if you wish to work part time and the number of preferred hours. Job share arrangements may be considered.

Requests for secondment from internal candidates may be considered on the basis that prior agreement has been sought from both your current line manager and the manager of your substantive post, if you are already undertaking a secondment role.

Informal enquiries may be addressed to Tania Dottorini, email [email protected] . Please note that applications sent directly to this email address will not be accepted.

It is a condition of this post that satisfactory enhanced disclosure is obtained from the ‘Disclosure and Barring Service’.

 

Further details:

  • Job Description/Role Profile

View Additional Information (this will open a new window)

Our University is a supportive, inclusive, caring and positive community. We welcome those of different cultures, ethnicities and beliefs – indeed this very diversity is vital to our success, it is fundamental to our values and enriches life on campus. We welcome applications from UK, Europe and from across the globe. For more information on the support we offer our international colleagues, see our Moving to Nottingham pages.

Applicants for this post will be considered on an equal basis, subject to the relevant permission to work in the UK as defined by the requirements set out by UK Visas & Immigration.  Please visit: https://www.gov.uk/government/organisations/uk-visas-and-immigration for more information.

For successful international applicants, we provide financial support for your visa and the immigration health surcharge, plus an interest-free loan to help cover the cost of immigration-related expenses for any dependents accompanying you to the UK. For more information please see the our webpage on Financial support for visas and the immigration health surcharge.

Requirements

Research Field
Biological sciences
Years of Research Experience
4 – 10

Research Field
Computer science
Years of Research Experience
4 – 10

Research Field
Computer science
Years of Research Experience
4 – 10

Additional Information

Website for additional job details
https://academicpositions.com

Work Location(s)

Number of offers available
1
Company/Institute
University of Nottingham
Country
United Kingdom
City
Nottingham
Postal Code
NG7 2RD
Street
University Park

Where to apply

Website
https://academicpositions.com/ad/university-of-nottingham/2023/research-fellow-…

Contact

City
Nottingham
Website
http://www.nottingham.ac.uk/
Postal Code
NG7 2RD

STATUS: EXPIRED

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