Job description & person
specification
Last updated:
26 October 2015
JOB DESCRIPTION
Post title:
Research Fellow in Modern Data Analytics
Academic Unit/Service:
Mathematics
Faculty:
Social Human and Mathematical Sciences
Career pathway:
ERE
*ERE category:
Research focused
Posts responsible to:
The PI and Co-Is of the Joining the Dots EPSRC project EP/N014189/1
Posts responsible for:
N/A
Post base:
Office-based
Level:
4
Job purpose
To conduct fundamental research in a suitable sub-area of topological data analysis, machine learning,
statistics and with applications to areas including asthma research and computational chemical discovery,
supported by the EPSRC grant EP/N014189/1.
Key accountabilities/primary responsibilities
% Time
1.
Develop a data analysis pipeline combining topology, machine learning, statistics, as
required.
30%
2.
Apply TDA to application areas in medicine, chemistry, as required.
30%
3.
Keep abreast with the latest developments in the field and write and present regular
progress reports
10%
4.
Take the lead in initiating publications
10%
5.
Work with other researchers in Mathematical Sciences and other research areas
5%
6.
Present the work at appropriate research conferences
5%
7.
Help with supervision and teaching of PhD and undergraduate students
5%
8.
Any other duties as allocated by the line manager following consultation with the post
holder.
5%
Key accountabilities/primary responsibilities
% Time
Special Requirements
Applications will be considered from candidates who are working towards or nearing completion of a
relevant PhD qualification. The title of Research Fellow will be applied upon completion of PhD. Prior to the
qualification being awarded the title of Senior Research Assistant will be given.
Internal and external relationships
PI and Co-Is: collaborative research work and regular meetings to discuss progress with PI and Co-Is and
their research groups
Liaison with the external academic and non-academic collaborators, partners, interested industry contacts
Active participation in the academic life of the faculties involved especially in the area of data science.
PERSON SPECIFICATION
Criteria
Essential
Desirable
Qualifications,
knowledge &
experience
PhD (or equivalent) and experience
in an appropriate area of
Mathematics, Computer Science,
Mathematical Biology,
Computational Chemistry
Strong interest in interdisciplinary
research on the boundary of
mathematics, statistics, machine
learning and applications
Detailed understanding and
knowledge in an appropriate area of
Mathematics, Computer Science,
Mathematical Biology,
Computational Chemistry
How to be
assessed
Knowledge of or experience in a
branch of data analysis specific to
medical or chemical research
Track record in interdisciplinary
projects
Research track record in one or
more of TDA, machine learning,
statistics
Proficiency in a programming
language e.g.: SAS, MATLAB, R,
python, etc.
Planning &
organising
Ability to conduct research both
independently and in collaboration
with peers
Ability to organise own research
activities to deadlines and quality
standards
Problem solving
& initiative
Ability to develop understanding of
complex problems and apply in
depth knowledge to address them
Management &
teamwork
Articulate and able to build good
working relationships with academic
and professional staff
Communicating
& influencing
Good communication skills, both
written and oral; ability to write up
research results for publication in
leading peer-reviewed journals
Other skills &
behaviours
Understanding of relevant Health &
Safety issues
Document1
2
Positive attitude to colleagues and
students
Special
requirements
National and international travel
JOB HAZARD ANALYSIS
Is this an office-based post?
☒ Yes
If this post is an office-based job with routine office hazards (eg: use of VDU), no further
information needs to be supplied. Do not complete the section below.
☐ No
If this post is not office-based or has some hazards other than routine office (eg: more than use
of VDU) please complete the analysis below.
Hiring managers are asked to complete this section as accurately as possible to ensure the safety
of the post-holder.
## - HR will send a full PEHQ to all applicants for this position. Please note, if full health clearance is required
for a role, this will apply to all individuals, including existing members of staff.
ENVIRONMENTAL EXPOSURES
Occasionally
Frequently
Constantly
(<30% of time)
(30-60% of time)
(> 60% of time)
Outside work
Extremes of temperature (eg: fridge/ furnace)
## Potential for exposure to body fluids
## Noise (greater than 80 dba - 8 hrs twa)
## Exposure to hazardous substances (eg: solvents, liquids, dust, fumes,
biohazards). Specify below:

Frequent hand washing
Ionising radiation
EQUIPMENT/TOOLS/MACHINES USED
## Food handling
## Driving university vehicles(eg: car/van/LGV/PCV)
## Use of latex gloves (prohibited unless specific clinical necessity)
## Vibrating tools (eg: strimmers, hammer drill, lawnmowers)
PHYSICAL ABILITIES
Load manual handling
Repetitive crouching/kneeling/stooping
Repetitive pulling/pushing
Repetitive lifting
Standing for prolonged periods
Repetitive climbing (ie: steps, stools, ladders, stairs)
Fine motor grips (eg: pipetting)
Gross motor grips
Repetitive reaching below shoulder height
Repetitive reaching at shoulder height
Repetitive reaching above shoulder height
PSYCHOSOCIAL ISSUES
Face to face contact with public
Document1
3
Lone working
## Shift work/night work/on call duties
Document1
4