Research Assistant/Research Associate in Inflammation and Computational Biology

Job description

This is an exciting opportunity to be a key member of a team that is researching the genomic origins of inflammatory disease and myeloid cancers.  We are studying clonal haematopoiesis or CHIP, where individuals acquire mutations in blood cells without apparent blood disease, and these mutations occur in haematopoeitic stem progenitor cells and mature blood cells.  CHIP is a potential point of origin of blood cancers including myelodysplastic syndrome (MDS) and acute myeloid leukaemia (AML) and also increases the risk of inflammatory conditions including atherosclerosis. 

 

Our research group is innovative and flexible.  We work in collaboration with others to address important translational/ clinical questions around blood cancers and inflammatory diseases, especially those associated with aging.  We use state-of-the-art multi-omic approaches including single cell techniques to study how mutations affect haematopoiesis and blood cell function, as well as established cytometric, proteomic and functional assays.   

 

We are seeking a motivated, skilled, and enthusiastic candidate to join our research team. The successful applicant will be expected to develop and undertake research of high quality consistent with the aims of the project.   

 

The applicant should have a sound knowledge of cellular and molecular biology, and preferentially a degree in this field.  We would like an applicant with aptitude and enthusiasm for computational analysis, with some experience of computational analysis of next generation sequencing data.  We are looking for a team member who is ready to face scientific challenges, who is able to work independently when required, but also fully integrate into a tea.  The successful candidate will also have excellent organisation, communication and presentation skills.   

 

Both postgraduate (pre-doctoral) and post-doctoral candidates are welcome to apply. A successful postdoctoral candidate can expect to be paid at Grade 6.   

 

We are especially interested in helping promising early stage researchers develop their career and encourage applications from those who see this post as a launchpad for their scientific ambitions.  This post will offer opportunities to expand on laboratory and bioinformatic skills, which we think will be excellent training for the successful candidate for their future scientific career.  We have helped secure PhD positions both at KCL and elsewhere for all postgraduate research assistants from our group since 2020.   

 

This post will be offered on a fixed-term contract initially until 26th July 2024, with the possibility of extension until 30th June 2025. 

This is a full-time post - 100% full time equivalent

 

Key responsibilities

•         Perform computational analysis of multi-omic data (e.g. genotyping/ variant calling, RNAseq; including single cell data).  

•         Perform statistical analysis of experimental data. 

•         Help with HTC data organisation and storage for the group, liaising with central HTC team at King’s. 

•         Plan own day-to-day research and administrative activities within the framework of the agreed research objectives and milestones. 

•         Keep detailed and accurate records of computational workflows, codes and pipelines. 

•         Work with non-specialists in the team to perform basic analysis of genomic data. 

•         Learn and develop new computational tools as required by the project. 

•         Work with collaborators, including clinicians, other research scientists and bioinformaticians as required by the project. 

•         Interact scientifically with other members of the group, present data at regular group meetings, represent the team at conferences. 

•         Support the training of undergraduate and postgraduate project students.  

•         Contribute to the preparation of grant applications and manuscripts for journal publication.  

•         Understand and respect data governance guidance, especially in the handling of patient data. 

 

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.  

Skills, knowledge, and experience 

RESEARCH ASSISTANT (Grade 5) 

Essential criteria

1.       BSc/ MSc in a relevant biomedical or biological sciences or bioinformatics.  The candidate has to demonstrate ability in key computational skills, statistics and a sound understanding of cellular and molecular biology.   

2.       Aptitude for bioinformatics, ability to learn programming skills, including in R and python.  

3.       Knowledge of variant calling (targeted gene panels, whole exome or genome sequencing), and analysis of RNAseq data.   

4.       Experience in statistical analysis, including study design. 

5.       Demonstrate ability to manage own research and administrative activities efficiently, prioritise, meet targets and deadlines. 

6.       Demonstrate ability to problem solve. 

7.       Ability to work independently and flexibly, and also work as part of a team. 

8.       Excellent interpersonal, presentation skills and communication skills, including the ability to communicate complex ideas to non-specialists. 

 

Desirable criteria

1.       Knowledge of single cell genomic/ multi-omic analysis  

2.       Knowledge of artificial intelligence approaches and big data analysis 

3.       Background in biology, preferably cellular and molecular biology, haematology or immunology. 

 

RESEARCH ASSOCIATE (Grade 6)

Essential criteria

1.    PhD/ DPhil in a relevant biomedical or biological sciences or bioinformatics.  The candidate has to demonstrate ability in key computational skills, statistics and a sound understanding of cellular and molecular biology.   

2.    Experience in bioinformatics, good programming skills, including in R and python.  

3.    Experience in variant calling (targeted gene panels, whole exome or genome sequencing), and analysis of RNAseq data.   

4.    Experience in statistical analysis, including study design. 

5.    Demonstrate ability to manage own research and administrative activities efficiently, prioritise, meet targets and deadlines. 

6.    Demonstrate ability to problem solve. 

7.    Ability to work independently and flexibly, and also work as part of a team. 

8.    Excellent interpersonal, presentation skills and communication skills, including the ability to communicate complex ideas to non-specialists. 

 

Desirable criteria

1.    Knowledge of single cell genomic/multi-omic analysis  

2.    Knowledge of artificial intelligence approaches and big data analysis 

3.    Background in biology, preferably cellular and molecular biology, haematology or immunology. 

 

Further information

We would like the successful candidate to start as soon as possible after the job offer (latest 1/7/2023).  

 

Planned interview dates: late April/early May.