PREPme: Prime REsearch Program for beginners in medical data analytics & learning


1 On 1 mentorship

PREPme (Prime REsearch Program) will equip you with knowledge and skills in machine learning and data analytics. You will get the opportunity to (i) learn from experts in the field, (ii) get one-on-one mentorship and (iii) contribute to the state-of-the-art by producing innovative frameworks that solve challenging healthcare problems.

Experience elite-performer flow

PREPme will help you unleash your potential in research, develop your knowledge and skills in the rapidly evolving field of artificial intelligence and machine learning, and achieve results that will make your CV stand out in the job market as well as when applying for international competitive Ph.D programs. We are one team and our motto is "CLARITY + ACTION = RESULTS".

Program Eligibility

A good knowledge of one or more of these programming languages (C++, MATLAB, Python)
[Must attend the program in its entirety]

Application Requirements

Please send your (1) CV and (2) personal statement – in a 500 word maximum essay, discuss your goals, values and reasons for wanting to join the program to before July, 5th 2019.

We are one team

Islem Rekik

Islem Rekik is an assistant professor (lecturer) within Computing at the University of Dundee. Previously, she was a postdoctoral research scholar at the IDEA lab (University of North Carolina) following a PhD in "Neuroimaging and Computer Sciences" from the University of Edinburgh in 2014. Currently, she is the director of BASIRA (Brain And SIgnal Research & Analysis, laboratory and a member of the Computer Vision & Image Processing (CVIP) group at the University of Dundee. Dr Rekik has more than 40 peer-reviewed research papers. She is a program committee member of leading international medical image analysis conferences and workshops including MICCAI, Machine Learning in Medical Imaging (MLMI), Connectomics in NeuroImaging (CNI), and Deep Learning in Medical Imaging (DLMI). She was appointed as an outstanding reviewer by the Computized Medical Imaging and Graphics journal in 2017, and the journal of Neuroscience Methods in 2015. Dr Rekik has also reviewed for prestigious research conferences (MICCAI, IPMI) and more than 15 high-impact journals including NeuroImage, Medical Image Analysis, PLOS ONE, Frontiers in Neuroscience, Pattern Recognition, and Artificial Intelligence in Medicine. Her research work aims to infuse advanced computer vision and machine-learning methods into big neuroimaging and signal data analysis for improving healthcare and wellbeing.

Can Gafuroğlu
(Final year undergrad student)

"My training has given me the tools and the confidence to understand and critically assess the contents of research papers so that I can direct my own research."
Research outputs:
C. Gafuroğlu et al. MICCAI 2018, Granada, Spain (international conference acceptance rate 30% ).
Sir James Black Award for outstanding research achievement —June 2018

Mayssa Soussia
(MSc student)

"My training did not only equip me with a strong knowledge in machine learning and teach me how to produce good research but also boosted my confidence and self esteem."
Research outputs:
M. Soussia et al. MICCAI Connectomics in Neuroimaging workshop 2017, Quebec Canada (Best Paper Award ).

Nesrine Bnouni
(Ph.D student)

"My training gave me the opportunity to explore and learn a wide range of machine learning and medical image analysis methods."
Research outputs:
N. Bnouni et al. ATSIP 2018, Sousse, Tunisia (Best Paper Award ).

FOCUS. SIMPLIFY. ACHIEVE. PREPme will awake your inner ability to create results.

PREPme 2019

Scope and context

The world is awash with big and complicated data, engineers and researchers are trying to make sense out of it. Leading examples include image and behavioural data from Facebook and Google, as well as medical and healthcare data where companies such as Toshiba and Siemens compete over finding ‘the best’ solution(s) to most challenging problems in big medical data analysis. This has led to an explosion of interest in the field of machine learning, where researchers ‘engineer’ methods that learn how to efficiently analyse, represent and interpret data. PREPme will give you a foundational understanding of several compelling machine learning methods, that were applied to address healthcare questions (e.g., what distinguishes a brain with dementia from a healthy brain?). However, what is distinctive about PREPme program is that it trains you to develop your program from scratch and get it published within a 12-week timeline.  

Learn from scratch

PREPme gives you the opportunity to directly learn from experts in the fields of machine learning and data analytics  via live teaching and mentorship. 

PREPme will equip you with tools and strategies that will allow you to address the three following questions.

  • How to read & understand a machine-learning paper from scratch (without any prior or advanced mathematical knowledge)?
  • How to come up with multiple creative solutions to a machine-learning problem using the ‘3-Bs strategy’Breaking, Blending, and Bending?
  • How to get your work/program published and become a Google scholar?


Early bird registration

12-week intensive training program
$ 0
  • Apply before July, 5th 2019 and get a free spot by sending your CV and cover letter to! Only 10 spots are available. Projects can start on January 1st, 2019 or later.

Become a PREPme member

12-week intensive training program
$ 500
  • PREP-me applications received after July, 5th 2019 will be charged 500$ for training. Please contact and save your spot!

Application opening date: 01/06/2019