modif

_includes/archive-single.html

@@ -32,12 +32,6 @@ <h2 class="archive__item-title no_toc" itemprop="headline">
     <p class="page__meta"><i class="fa fa-clock-o" aria-hidden="true"></i> {% include read-time.html %}</p>
     {% endif %}
 
-      {% if post.collection == 'education' %}
-        <p> {{ post.type }}, <i>{{ post.venue }}</i>, {{ post.date | default: "1900-01-01" | date: "%Y" }} </p>
-      {% elsif post.collection == 'publications' %}
-        <p>Published in <i>{{ post.venue }}</i>, {{ post.date | default: "1900-01-01" | date: "%Y" }} </p>
-      {% elsif post.date %}
-        <p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> {{ site.data.ui-text[site.locale].date_label | default: "Published:" }}</strong> <time datetime="{{ post.date | default: "1900-01-01" | date_to_xmlschema }}">{{ post.date | default: "1900-01-01" | date: "%B %d, %Y" }}</time></p>
-      {% endif %}
+
   </article>
 </div>

_projects/2019-11-IP.md

@@ -12,7 +12,7 @@ tags:
   - Remote GPU/CPU clusters
 ---
 
-**2019-11 to present**, Institut Pasteur, Paris
+2019-11 to Present, Institut Pasteur, Paris
 
 The aim of this project is to enhance the quality of super-resolution images using deep learning techniques, with the goal of reducing the number of acquired single-molecule images. Accelerating acquisitions could enable high-resolution visualization of biological structures in living cells, particularly dynamic microtubules.