Research Manager

Job Description

Job description 

This role is open to applicants who have experience in collecting, analysing, and reporting primary qualitative and quantitative research data.

The project will be managed by the Schools of Chemistry at Imperial College London (Charlotte Sutherell), King?s College London (Helen Coulshed), University College London (Anna Roffey), University of Glasgow (Frances Docherty).You will be managing 2 student research assistants in a research project that aims to understand the main barriers and enablers to a successful transition from school onto a chemistry degree program and how staff and student opinions differ. 

Main duties and responsibilities:

 

  • Train student researchers on how to effectively review current literature on transition into university as it relates to lab-based degrees
  • Support student researchers to write copy advertising the opportunity to participate in research via survey completion.
  • Ensure all issues raised by paper.io are dealt with promptly.
  • Teach student researchers how to perform qualitative and quantitative data analysis 
    • choosing appropriate statistical tests, 
    • show them how to use relevant software e.g. SPSS and NVIVO
  • Facilitate discussion and collation of focus group themes.
  • Train student researchers on how to give effective and respectful interviews. 
  • Ensure that data collection and analysis is happening consistently and within the research project timeline. 
  • Ensure data collection and management is in accordance with GDPR guidelines and data transfer agreement.
  • Present findings to research group and key university stakeholders.
  • Co-create a toolkit to onboard chemistry students into university. 
  • Undertake any other reasonable duties as required by the team.

 

The role is fractional (0.1FTE January-July 2025). Hours of work will predominantly be scheduled remotely between Monday-Friday, 09.00-17.00 with some on campus meetings as needed and with prior agreement. There will be flexibility in how your hours are spread and you will be expected to manage your own workload depending on activity.

Any questions about the role please email helen.coulshed@kcl.ac.uk 



Qualifications

Physical science or lab based degree.



Skills

Experience/Skills required

  • Strong interpersonal skills. 
  • Ability to build relationships with a wide range of people from different backgrounds.
  • Experience in managing own workload, planning, and organising projects or activities independently.
  • Excellent communication skills and able to present ideas clearly.
  • Ability to adhere to GDPR and ethical guidelines and to follow data storage security protocols.
  • Experience of literature searching.
  • Experience of reference management software.
  • Experience conducting focus groups (in person or online)
  • Experience of statistical analysis software (e.g. SPSS)
  • Experience using qualitative data analysis software (e.g. NVIVO).
  • Knowledge and experience of analysing primary qualitative data using reflexive or inductive thematic analysis. 
  • Experience of audio recording and transcription software.
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The applicant will support an educational research project in the Faculty of Dentistry, Oral and Craniofacial Sciences. The research involves analysing data collected from a dashboard including teacher feedback, student feedback and self-reflections.

The role includes conducting thematic analyses and working with quantitative data. The successful candidate will be supported in developing their qualitative and quantitative research skills through guidance towards self-directed learning resources and ad-hoc training to enhance their expertise. 

The Research Assistant will contribute to generating meaningful insights to inform educational practices, particularly in assessment and feedback.

Key responsibilities:

  1. Clean, process and manage datasets from multiple excel sources for analysis.
  2. Provide quantitative and qualitative research support.
  3. Assist in conducting thematic analyses to identify themes from qualitative data.
  4. Perform quantitative analysis of student grade performance.
  5. Participate in discussions, communicating and presenting research at meetings.
  6. Contribute to writing reports, presentations and academic publications.


Qualifications

A third-year undergraduate student or above in any subject area.



Skills

Desirable skills: 

  1. Knowledge of qualitative and quantitative research methods and techniques 
  2. Some understanding of thematic analysis and experience in working with large datasets. 

Required skills:

  1. Basic knowledge of excel.
  2. Ability to work independently and collaboratively remotely.
  3. Ability to manage tasks and deliver results under tight deadlines.
  4. Strong work ethic, commitment to data accuracy.
  5. Ability to work with limited supervision.

To provide practical and emotional support to assist a student on the autism spectrum in taught sessions (lectures, seminars and labs). To support the student with explaining tasks and providing mutual regulation strategies that will ensure widening participation and access, academic progress and student retention in compliance with the Equality Act and the mission of Student Services.

This role is 9.5 hours a week distributed as below:

  • Monday 2.5 hours: 10-11am; 12-1pm (IT class); 2pm-3:30pm
  • Tuesday 3 hours: 11-1pm; 4-5:30pm
  • Wednesday 1.5 hours: 9- 11am
  • Thursday 1.5 hours: 10-11:30am (lab)

There will be breaks in between taught sessions.



Qualifications

Minimum of 5 GCSEs (or equivalent) at Grade A-C including English and Mathematics - Essential
A level qualifications (or equivalent), or equivalent relevant experience - Essential
Educated to degree level in a relevant field or equivalent experience - Desirable 
Relevant further educational or professional qualifications e.g. Mental Health First Aid. - Desirable
 



Skills

Experience

  • Experience of studying in Higher Education - Essential
  • Knowledge of autism spectrum condition - Desirable
  • Some experience/understanding of providing support for individuals on the Autism Spectrum - Desirable

Skills

  • Knowledge of SCERTS/Autism Spectrum Condition - Desirable
  • Mutual Regulation strategies: e.g. deep pressure techniques, grounding and breathing strategies - Desirable
  • Thorough knowledge of the campus - Essential
  • Awareness of disability issues ? recognising the most effective method of communicating during periods of dysregulation - Essential

Attitude

  • Outgoing; great interpersonal skills - Essential
  • Must be able to work calmly under pressure - Essential
  • Must be able to support and manage fluctuating behaviours - Essential
  • Must be willing to attend relevant training sessions arranged by the Disability and Dyslexia Service - Essential

Other - All essential

  • Flexible working timetable
  • This post is subject to a basic DBS check.
  • The ability to meet UK ?right to work? requirements

Job Title:  Digital Fingerprinting Feature Engineering 

Nvidia CSIT Cyber-AI hub intern in feature engineering (up to a maximum of 15 hours per week for 20 weeks). 

The successful candidate will be working as an intern with the Nvidia CSIT Cyber-AI Hub project team on preparing data from multiple sources for AI training. This includes proper data storage, organization, cleaning and feature engineering/preprocessing tasks. 

The candidate will help to improve the current feature selection and engineering process for the development of the behavioral model proposed by the team. In addition, and upon obtaining successful results, the candidate is expected to assist with the integration of the software in the Nvidia Morpheus github page. 



Qualifications

Degree in Computer Science or in a relevant field. 

Have, or be about to obtain an artificial intelligence related postgraduate degree. 



Skills

Essential criteria: 

In depth knowledge of Artificial Intelligent/Machine Learning concepts 

Experience in data management for AI training. 

Understanding in networking and security best practices. 

Strong programming skills (Python) 

Proficient Linux/Windows skills. 

Desirable criteria: 

Experience with ML projects including feature engineering 

Understanding of cyber security concepts, e.g. Cyber Kill Chain and Defense-in-depth. 

Knowledge in the MITRE ATT&CK framework and other threat modelling tools. 

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