From 61e77fa2e115171e780d7ca7715b2dcb15d15772 Mon Sep 17 00:00:00 2001
From: ncardozo <n.cardozo@uniandes.edu.co>
Date: Tue, 19 Dec 2023 07:53:58 -0500
Subject: [PATCH] removing old vacancy

Signed-off-by: ncardozo <n.cardozo@uniandes.edu.co>
---
 vacancies.html | 35 -----------------------------------
 1 file changed, 35 deletions(-)

diff --git a/vacancies.html b/vacancies.html
index 7c154ee2f..5e793f716 100644
--- a/vacancies.html
+++ b/vacancies.html
@@ -31,38 +31,3 @@ <h2>Ph.D. Teaching Assistant Position</h2>
 </p>
 <br/><br/>
 
-<p>
-    <h2>Ph.D. Research Assistant Position</h2>
-</p>
-<br>
-
-<p>
-   <b>Description:</b>
-   We are looking for motivated people to join us as Ph.D. students. The candidates will join the lively research environment of The Software Design Lab and FLAG lab for  a truly interdisciplinary research experience in both software engineering and artificial intelligence/machine learning.  
-   The current positions are open to work on the topic of e-learning in the context of an industrial Ph.D., in which the candidate will be required to participate actively in the activities of the industrial partner. 
-   <br><br>
-    <b>Research topic:</b>
-    The candidates will work on the general area of automated learning trajectories with aid of state-of-the-art machine learning techniques.  
-    The research project for the candidates will focus in the automation of learning trajectories using multiple online resources to maximize the learner's experience and subject comprehension. The main objective of the project is divided into three different axes  reconciling and integrating different areas of artificial intelligence:   
-    <ul>
-        <li> Knowledge representation: will be used to describe (e.g., using ontologies) and structure (e.g., through knowledge graphs) different learning resources for a given topic or subject of study.  </li>
- 
-        <li> Natural language processing: will be used for topic classification an to organize learning resources in different coherent trajectories based on difficulty, prerequisites, or popularity in usage by successful learners.  </li>
- 
-        <li> Machine learning: will be used to categorize and optimize trajectories based on information gathered from multiple other learners. </li>
- 
-        <li> Recommender systems: will be used to suggest appropriate trajectories for  learners, taking into account their past performance and learning pace. </li>
- 
-        <li> Software engineering: will be used to deploy the models on a real software solution that will serve daily thousands of users. </li>
-    </ul>    
-    The work will be made concrete with the implementation of a learning platform to host learning resources, trajectories, and user information, together with a mobile application to maximize learners' accessibility and engagement with the material.  
- 
-The positions are offered for 4 years, as a research assistant part of the project. The position will cover tuition and stipend. 
-<br><br>
-    <b>Requirements:</b>
-    Applicants should hold a Master degree in computer science or a related discipline (with a strong computing component/knowledge), demonstrating to be at the top of your class, and prove english proficiency and scientific writing.  
-    Note that we have a continuous application process. You are able to apply to the Ph.D. program at any moment, but you are required to follow the vetting process of the admission requirements at Universidad de los Andes.
-Information about the Ph.D. program: <a href="https://ingenieria.uniandes.edu.co/es/posgrados/doctorados/doctorado-ingenieria">https://ingenieria.uniandes.edu.co/es/posgrados/doctorados/doctorado-ingenieria</a>
-    <br><br>
-    Contact information: n.cardozo at uniandes dot edu dot co
-</p>