Imperial College London
Job Description
Job Title:
Research Associate
Department/Section:
Centre for Synthetic Biology and Innovation,
Department of Bioengineering, Faculty of Engineering
Location:
Bessemer Building, South Kensington Campus
Level/Job Family:
Level B, Academic & Research
Reporting to:
Dr Guy-Bart Stan
Working closely with:
“Control Engineering and Synthetic Biology” group of
Dr Stan; other academic, research staff and students
within the Centre and the Department; administrative
and technical support staff
Working Hours:
Normally not less than 35 hours per week
Fixed Term:
14 months
Purpose of Role for the project “Data-based optimal control of synthetic
biology gene circuits”
(1) To carry out a programme of novel research in data-based optimal control applied
to synthetic biology gene circuits (in particular development and application of novel
reinforcement learning methods for the optimal control of gene circuits based on
measured input-output data from these circuits) and (2) to undertake project
management and supervise multi-disciplinary teams. The project will be a
programme of research that will fit into the main research themes of Imperial’s Centre
for Synthetic Biology and Innovation which are (i) to build foundational tools for the
robust and optimal control of synthetic biology circuits, and (ii) to derive applications
using synthetic biology (e.g. engineering design and control of gene regulatory
devices, biosensors, metabolic control). It will involve close interaction with groups
with expertise in nonlinear dynamical systems theory and control, biomathematics,
and synthetic/systems biology. There will be regular meetings between the groups
involved.
In addition, the PDRA will be expected to submit publications to refereed journals and
international conferences. The project will involve investigations in the robust and
optimal control of synthetic biology systems with the ultimate goal of developing an
input/output data-based framework for the optimal control of synthetic biology gene
circuits. This will include the definition of some optimal control problems of interest
(e.g., moving towards/controlling around a desired steady state, and tracking of a
reference trajectory, both while simultaneously minimising the energy/resources
needed to do so) and the development and application of reinforcement-learning
methods which, based on measured input-output data, can reliably provide a
(sub)optimal solution for the considered problem (e.g., an appropriate sequence of
actions/inputs leading, through the optimisation of an a priori defined reward/cost
function, to the desired optimal behaviour as observed at the outputs of the
considered system).
Research Duties:
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to work in close cooperation with Dr Stan as formal supervisor, other research
staff, students and collaborators on the project
to submit publications to refereed journals
to present findings to colleagues and at conferences
to take initiatives in the planning of research
to contribute in writing bids for research grants
to work as part of a team and to be open-minded and cooperative
to generate and display results and interpret their implications
to produce accurate report-ready data and to assist in the preparation of written
progress reports as required
to maintain accurate and complete records of all findings
to help with the teaching and administration of the research group
to undertake instruction of PhD students as agreed
to provide guidance to staff and students
to direct the work of small research teams including undergraduate and
postgraduate students and to motivate others to produce a high standard of work
to attend progress and management meetings, regular laboratory meetings,
journals clubs and internal and external seminars, as required
to attend relevant workshops and conferences as necessary to develop contacts
and research collaborations within the College and the wider community
to help with the planning and design of appropriate experiments and to identify
and develop suitable techniques for the collection and analysis of data
to take responsibility for organising resources and effective decision making in
support of research
to promote the reputation of the Group, the Department and the College
to perform other reasonable tasks related to the furtherance of the project aims
Other Duties:
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to undertake appropriate administration tasks
to attend relevant meetingsto undertake any necessary training and/or
development programme
any other duties commensurate with the grade of the post as directed by line
manager / supervisor
to comply with relevant College policies, including Financial Regulations, Equal
Opportunities Policy, Promoting Race Equality Policy, Health and Safety Policy,
Information Systems Security Policy and Intellectual Property Rights and Register
of Interests Policies
Imperial College London is committed to equality of opportunity and to
eliminating discrimination. All employees are expected to adhere to the
principals set out in its Equal Opportunities in Employment Policy, Promoting
Race Equality Policy and Disability Policy and all other relevant
guidance/practice frameworks.
Job descriptions cannot be exhaustive and the post-holder may be required to
undertake other duties, which are broadly in line with the above key
responsibilities.
Person Specification
Applicants are required to demonstrate that they possess the following attributes.
Qualifications
Essential:
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Applicants should hold a PhD in Computer Science, Control Engineering,
Machine Learning, Computational Biology or closely aligned disciplines, or an
equivalent level of professional qualifications and experience.
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Previous experience in optimal control, sequential decision-making, multistage stochastic programming, nonlinear dynamical systems, stochastic
modelling of gene expression or equivalent research, industrial or commercial
experience.
Knowledge / Experience
Essential:
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Research experience in Reinforcement Learning / Optimal Control /
Sequential Decision Making / Multi-Stage Stochastic Programming
Experience in:
 Modelling, analysis and simulation of nonlinear dynamical systems in
biology -- stochastic and deterministic
Knowledge of:
 Key concepts in systems biology, metabolic networks and genetic
regulation networks
 Programming in relevant high level programming languages (Matlab®,
Mathematica®, R), and in C/C++
 The mathematical theory underlying stochastic processes and
nonlinear dynamical systems
Experience in some of the following techniques:
 Handling of large and structured data sets
 Logical or qualitative modelling of biological systems, in particular
gene regulation networks and metabolic networks
A successful track record in academic publications
Ability to work effectively with researchers from a broad range of disciplines
Desirable:
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Research experience in a Synthetic Biology environment
Experience in:
 Supervising or helping with the supervision of research students
 Conducting a detailed review of recent literature
 Competent deployment of numerical and simulation methods
 Analysis of biological data
 Collaborating with experimental biomedical scientists
Knowledge of:
 Gene regulation in prokaryotes
 Light inducible gene expression systems
Skills and Abilities
Essential:
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High level of analytical capability
Ability to develop and apply new concepts and methods
Computational capabilities (scientific programming, modelling, analysis,
control, sequential decision making, multi-stage stochastic programming)
Willingness to work as part of a multidisciplinary team and to be open-minded
and cooperative
Creative approach to problem solving
Excellent verbal communication skills and the ability to communicate complex
information clearly
Strong written communication skills and the ability to write clearly and
succinctly for publication
Ability to direct the work of a small research team and motivate others to
produce a high standard of work
Ability to organise own work with minimal supervision
Ability to prioritise own work in response to deadlines
Ability to work autonomously and show initiative with research
Discipline and regard for confidentiality and security at all times
Willingness to undertake any necessary training for the role
Commitment to meeting deadlines
Flexible attitude towards work
The appointee will be expected to display a high level of motivation, and to be
a career-oriented person
Desirable:
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Willingness to travel both within the United Kingdom and abroad to conduct
research and attend conferences/workshops and other meetings
Ability to assess resource requirements and deploy them effectively
Ability to encourage research culture in others