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@@ -40,7 +40,7 @@ <h2>Fluid: A Programming Language for Transparent, Self-Explanatory Research Out
 
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-      <h3 class="title lowercase">Cambridge MPhil/Part III 2024-25 Projects</h3>
+      <h3 class="title lowercase">Cambridge MPhil/Part III<br> 2024-25 Projects</h3>
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       <p>Fluid is an exciting opportunity to work on new programming language foundations designed to make
@@ -55,41 +55,40 @@ <h4>Project description</h4>
       the visual artifacts we are actually presented with are opaque: any relationship to the underlying data
       is lost. How can we expect to understand, critique or evaluate claims based on a bitmap? This is
       challenging enough for an expert with access to the source code and data used to derive the outputs; for
-      a non-expert the prospects are even worse.
+      a non-expert the prospects are even worse.</p>
 
-      <a href="f.luid.org">Fluid</a> is a new “transparent” programming language, being developed at the
+      <p><a href="f.luid.org">Fluid</a> is a new “transparent” programming language, being developed at the
       Institute of Computing for Climate Science in Cambridge in collaboration with University of Bristol,
       that makes it easy to create charts and figures which are linked to data, enabling a user to
       interactively discover what visual elements actually represent. The key idea is to incorporating a
       bidirectional dynamic dependency analysis into the language runtime, allowing it to track dependencies
-      that arise as as outputs (such as charts and tables) are computed from data. It uses this information to
-      automatically enrich rendered output with interactions that allow a reader to explore the relationship
-      to data directly through the artefact, by selecting visual features of interest. Fluid uses so-called
-      “program slicing” techniques based on Galois connections, a neat mathematical abstraction which
-      characterises exactly the relationship between sets of inputs and sets of outputs which depend on
+      that arise as as outputs (such as charts and tables) are computed from data. This information is then
+      used to automatically enrich rendered output with interactions which allow a reader to explore the
+      relationship to data directly through the artefact, by selecting visual features of interest. Fluid uses
+      so-called “program slicing” techniques based on Galois connections, a neat mathematical abstraction
+      which characterises exactly the relationship between sets of inputs and sets of outputs which depend on
       them.</p>
 
       <p>The live demos on the website show the interactive queries we currently support, but these only
-      scratch the surface of what this kind of infrastructure makes possible. There are many opportunities for
-      an imaginative and technically strong student to help move this idea forward. Your project could go in a
-      number of directions, depending on whether your interests lie more towards programming languages, formal
-      methods or data science. A programming languages project would extend Fluid into a literate programming
-      tool, by adding Markdown support and the ability to embed computational content via a Lisp-style
-      backquote mechanism. A more mathematical project might add multidimensional arrays to the language,
-      along with various array operations inspired by linear algebra and an extension of the dependency
-      analysis to these new operations. A project focused more around science communication would use Fluid to
-      adapt a piece of real-world climate science into a “long-form” essay or interactive explanation intended
-      for a non-specialist audience. (See <a href="https://distill.pub">distill.pub</a> for some
-      examples.)</p>
+      scratch the surface of what this kind of infrastructure should make possible. There are many
+      opportunities for an imaginative and technically strong student to help move this idea forward. Your
+      project could go in a number of directions, depending on whether your interests lie more towards
+      programming languages, formal methods or data science. A programming languages project would extend
+      Fluid into a literate programming tool, by adding Markdown support and the ability to embed
+      computational content via a Lisp-style backquote mechanism. A more mathematical project might add
+      multidimensional arrays to the language, along with various array operations inspired by linear algebra
+      and an extension of the dependency analysis to these new operations. A project focused more around
+      science communication would use Fluid to adapt a piece of real-world climate science into a “long-form”
+      essay or interactive explanation intended for a non-specialist audience. (See <a
+      href="https://distill.pub">distill.pub</a> for some examples.)</p>
 
-      <p>If you think this sounds interesting, please get in touch and we can arrange an initial meeting.
-      Whatever form your project takes, we would aim for your work to be incorporated into our main
-      development codebase, and so would form a genuine contribution to a new programming language. You will
-      get to present your work to researchers and data scientists at the Institute of Computing for Climate
-      Science and The Alan Turing Institute, and work with PhD students at Cambridge and Bristol. A strong
-      background in functional programming, maths and/or science is a must. You can expect to gain experience
-      in programming languages research, data analysis and data visualisation, with close supervisor
-      support.</p>
+      <p>If you think this sounds interesting, please get in touch to arrange an initial chat. Whatever form
+      your project takes, we would aim for your work to be incorporated into our main development codebase,
+      and so would form a genuine contribution to the overarching project. You will get to present your work
+      to researchers and data scientists at the Institute of Computing for Climate Science and The Alan Turing
+      Institute, and work with PhD students at Cambridge and Bristol. A strong background in functional
+      programming, maths and/or science is a must. You can expect to gain experience in programming languages
+      research, data analysis and data visualisation, with close supervisor support.</p>
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