Vacancy Information

Machine Learning and Genomics Informatician (3 year fixed term contract)

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Location: Cambridgeshire
Closing date: 27 Aug 2020
Reference number: T/369

Job details

NIAB is the UK’s fastest growing crop science organisation, with rapidly expanding research capabilities in plant genetics, agronomy, farming systems and data science, the largest national field trials capability, and strong research links with industry, Government and academia. With headquarters in Cambridge, and regional offices across the country, employing around 400 people across the UK, NIAB provides scientific research, technical services and practical advice to improve the yield, efficiency and resilience of crop production across the arable, forage and horticulture sectors.

Pathogens are a constant threat to society and in the past have led to profound changes to our civilisation. Despite many advances in disease control, plant pathogens remain of great concern to the security of our food production, but the predication of the host range and pathogenic ‘potential’ of microbes remains elusive.

Working with the data sciences and pathology departments, NIAB is seeking a talented and motivated postdoctoral Informatician to investigate machine-learning approaches to predict host range from genome sequence using the bacterial plant pathogen Pseudomonas as a model, building on previous work- e.g. Hulin et
al. (https://doi.org/10.1111/ppa.13189, https://doi.org/10.1111/nph.15182, https://doi.org/10.1111/ppa.12834).

The Essential requirements for this role are:
• A PhD in bioinformatics or other scientific discipline which has included activities in bioinformatics, data analysis or computer sciences is preferred, but in exceptional circumstances non-PhD candidates will be considered
• A degree in a Biological, Mathematical and/or Computational Science
• At least 2 years of working experience in developing software in Informatics or Computational Biology
• Strong background in machine learning/deep learning or requisite mathematical skills to learn
• Strong programming skills in Python or other appropriate language
• Familiarity with Unix command line
• Attention to detail and ability to solve scientific problems
• Work independently or with minimal supervision
• Excellent communication and interpersonal skills

The Desirable requirements for this role are:
• Demonstrable experience of leading the development of novel machine learning tools and methodologies
• Extensive experience in artificial intelligence/machine learning field
• Detailed knowledge of machine learning languages eg. Tensorflow, PyTorch
• Familiarity with the use of job scheduling systems for the use of High Performance computing
• Use of version control (github)
• Ability to work effectively in collaborative environment
• Enthusiastic to learn and help the scientific community

Additional guidance by senior data scientists in the Data Sciences department will be provided.  NIAB will also provide unique computational infrastructures designed for big-data analytics, deep learning and algorithmic development, through which your knowledge and skills in AI and data sciences will be strengthened.

Using supervised machine learning and deep learning (so-called AI) approaches the post holder will deploy a variety of methods to identify signatures of host adaptation present in the genome of Pseudomonas which will be experimentally verified.
Prior experience in the use of various classification and regression techniques eg:
• Support vector machines
• Random forests
• Convolutional Neural Networks
as well as experience with high level languages and environments Python, Tensorflow, R etc.

You will work collaboratively with wet-lab scientists producing data and participate in the research activities of the institution as a whole. You will be expected to contribute their own innovative ideas, resulting in potential independent projects. The postholder will be expected to write scientific research papers and present results at conferences.  You must be comfortable working at the interface of disciplines in a constructive and collaborative manner.

NIAB has formed an alliance with the University of Cambridge, the Crop Science Centre, to carry out outstanding and impactful science for the equitable and sustainable transformation of agriculture. You would be working as part of the alliance, which receives funding from both national and international sources (e.g. Bill & Melinda Gates Foundation). In joining NIAB you will be part of the Cambridge landscape of Plant and Crop Sciences, associating with colleagues in the department of Plant Sciences and the Sainsbury Laboratory.

The post is initially available for 3 years, with the possibility of extension subject to available funding. Salary is in the range of £30,342 to £40,036 per annum, depending on experience and qualifications along with 25 days annual leave plus 8 days public holidays, pleasant working environment and eligibility to join the company pension scheme upon appointment.

Informal enquiries to Dr Richard Harrison- Richard.harrison@niab.com.  Further details and an application form are available at: https://www.niab.com/careers or from the HR Office, NIAB, 93 Lawrence Weaver Road, Cambridge CB3 0LE, Tel No. 01223 342282, Email: jobs@niab.com, quoting Ref No. T/369.  Closing date for applications: 27 August 2020 with interviews to be held w/c 7 September 2020 either via Zoom/MS Teams or Face-To-Face.

JOB DESCRIPTION