Machine Learning/Bioinformatics Postdoc Researcher
The King’s College London British Heart Foundation (BHF) Centre of Research Excellence is designed to nurture interdisciplinary collaborations and bench-to-bedside projects in cardiovascular research. The Faculty of Cardiovascular Medicine & Sciences is a core constituent of the BHF Centre where the cardiovascular proteomics group is led by Prof. Manuel Mayr and the bioinformatics team is led by Dr. Konstantinos Theofilatos. The cardiovascular proteomics research group (http://www.vascular-proteomics.com/) is a state-of-the-art laboratory and has the latest mass spectrometry equipment, established computational infrastructure and high experience in proteomics and multi-omics cardiovascular research analysis projects.
This position is referring to the approved BHF Project Grant “Harnessing machine learning for a multi-omics approach to cardiovascular disease” with the (PG/20/10387) of the Principal Investigators Dr. Konstantinos Theofilatos and Prof. Manuel Mayr. In the context of this Project multi-omics datasets that have already been developed by the Cardiovascular Proteomics Lab will be used to develop biosignatures and models for the assessment of cardiovascular risk as well as the diagnosis and prognosis of cardiovascular diseases including Myocardial Infarction and Atherosclerosis. The post-doctoral researcher will assist in the development of the novel machine learning and network analytics methods, proceed in their parallelization and their adjustment to make them compatible with cloud computing infrastructure, and assist in the overall analysis of the multi-omics data of the project. The hired researcher will collaborate for 6 months Prof. Chenlei Leng from the University of Warwick (https://warwick.ac.uk/fac/sci/statistics/staff/academic-research/leng/) for the development of co-expression network reconstruction techniques and other statistical analysis related tasks of the project.
Applicants must hold a PhD in Bioinformatics/Machine Learning (or an equivalent scientific degree), be highly motivated, independent and senior enough to organise the work of students and integrate themselves into a team. Applicants must be experienced python programmers and have prior experience in parallelization and working with high performance computing infrastructures. Knowledge of cardiovascular diseases or Proteomics is desirable but not essential.
When applying, please attach a personal statement to tell us why you are suitable for the role.
If you have questions about this role, please contact: Dr. Konstantinos Theofilatos, Email: firstname.lastname@example.org
This post will be offered on an a fixed-term contract for 2 years
This is a full-time post - 100% full time equivalent
- Design and develop new dimensionality reduction/classification hybrid methods and pipelines for biomarker discovery from multi-omics datasets
- Design and develop new co-expression network construction methods
- Optimize, parallelize machine learning methods implementation and make them compatible for high performance computational infrastructures
- Perform statistical and bioinformatics analysis on multi-omics cardiovascular research related datasets from plasma, serum and tissue samples
- Visualize the results of analysis using scripting languages
- Supervise and coordinate students in machine learning and bioinformatics related projects
- Assist in the establishment and maintenance of a cloud computing infrastructure
- Contribute to writing high impact scientific manuscripts
Skills, knowledge, and experience
- PhD in Bioinformatics, Machine Learning or an equivalent scientific degree
- Ability to work effectively with multidisciplinary teams composes of bioinformaticians, molecular scientists, clinicians and biostatisticians
- Previous experience on machine learning and bioinformatics
- First author publication record in bioinformatics and/or machine learning related manuscripts
- Experience in working with high performance computing infrastructure
- Experience in working with scripting programming languages (Python and R)
- Ability to work independently and balance competing priorities under pressure of deadlines and workloads
- Good organisational and time management skills- strong planning and organisational skills including the ability to prioritise, manage multiple tasks
- Excellent oral and written communication skills
- Previous experience in cardiovascular research
- Previous experience in analyzing mass spectrometry proteomics datasets
* Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.
Applications from junior and senior postdoctoral researchers are welcomed for this position. The salary will be paid at Grade 6, £41,517 per annum, including London Allowance.
The selection process will include a panel interview and a presentation.
This post is subject to Disclosure and Barring Service.