Research Fellow - Institute of Cancer and Genomic Sciences - 104098 - Grade 7

TN United Kingdom; United Kingdom; On-site; GBP 40,000 - 70,000; Full time

Job summary

An innovative research opportunity awaits you in a multidisciplinary team focused on advancing the field of neuroscience and machine learning. This post-doctoral position emphasizes the development of cutting-edge AI methods to tackle clinical challenges, particularly through the integration of multi-modal data. Collaborating with leading experts, you will contribute to significant research objectives, engage in mentorship, and disseminate findings to the broader community. This role is perfect for those passionate about leveraging technology in healthcare and eager to make a meaningful impact in a supportive and inclusive environment.

Qualifications

• PhD or near completion in Data Science, AI, or related fields.
• Experience in developing machine learning methods for clinical challenges.

Responsibilities

• Develop novel computer-based models and techniques.
• Analyze and interpret data for research objectives.
• Disseminate findings through publications and seminars.

Skills

Machine Learning

Artificial Intelligence

Python

Data Analysis

Explainable AI

Statistical Analysis

Communication Skills

Education

PhD in Data Science

PhD in Computer Science

Tools

NumPy

SciPy

Pandas

scikit-learn

TensorFlow

PyTorch

Hugging Face

Job description

Research Fellow - Institute of Cancer and Genomic Sciences - 104098 - Grade 7, United Kingdom

Client:

University of Birmingham

Location:

Job Category:

Other

EU work permit required:

Yes

Job Reference:

Job Views:

12

Posted:

28.04.2025

Expiry Date:

12.06.2025

Job Description:

Summary

This post-doctoral research position will be conducted in collaboration with a multidisciplinary team of experts in neuroscience, immunology, pain, anesthesia, and machine learning. The team also aims to recruit additional post-doctoral research associates, a research technician, a research assistant, and a research nurse.

Supervision will be provided by Dr. Andreas Karwath, Dr. Ali Mazaheri, Prof. Fang Gao Smith, and Dr. Helen McGettrick.

The successful candidate should have a strong background in computer science, state-of-the-art machine learning, artificial intelligence, and multi-modal data integration. Experience with explainable machine learning/AI approaches in medical or clinical settings, especially in combining modalities like EHR, biomarkers, longitudinal data, multi-omics, EEGs, NLP, is highly advantageous.

Main Duties

• Developing novel computer-based models, techniques, and methods.
• Develop research objectives and proposals, potentially with mentorship.
• Contribute to writing research funding bids.
• Analyze and interpret data.
• Apply knowledge to develop new intellectual understanding.
• Disseminate research findings through publications and seminars.
• Supervise students and guide PhD candidates where appropriate.
• Manage administrative tasks related to research.
• Participate in departmental research activities and administration.
• Engage in enterprise, business development, and public engagement activities.
• Collect research data via various methods such as experiments, literature reviews, and interviews.
• Present research outputs at seminars and conferences.
• Guide support staff and students assisting with research.
• Address problems impacting research objectives and deadlines.
• Promote equality and foster an inclusive working environment.

Person Specification

• PhD (or near completion) in (Health) Data Science, Computer Science, AI, or related fields. Candidates with healthcare-related PhDs with strong ML/AI skills are encouraged to apply.
• Proven experience in developing cutting-edge machine learning/AI methods for clinical challenges, with emphasis on multi-modal data and explainable AI.
• Proficiency in Python and familiarity with libraries such as NumPy, SciPy, Pandas, scikit-learn, TensorFlow, PyTorch, Hugging Face.
• Experience with High Performance Computing and Linux systems.
• Strong analytical skills.
• Ability to publish and present research findings effectively.
• Excellent communication skills across disciplines.
• Self-motivated and flexible work approach.
• Ability to plan and organize research activities.
• Knowledge of the Equality Act 2010 and commitment to fair treatment of all protected characteristics.