<html xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
<meta name="Generator" content="Microsoft Word 15 (filtered medium)">
<style><!--
/* Font Definitions */
@font-face
{font-family:Wingdings;
panose-1:5 0 0 0 0 0 0 0 0 0;}
@font-face
{font-family:"Cambria Math";
panose-1:2 4 5 3 5 4 6 3 2 4;}
@font-face
{font-family:Calibri;
panose-1:2 15 5 2 2 2 4 3 2 4;}
/* Style Definitions */
p.MsoNormal, li.MsoNormal, div.MsoNormal
{margin:0cm;
margin-bottom:.0001pt;
font-size:11.0pt;
font-family:"Calibri",sans-serif;
mso-fareast-language:EN-US;}
h3
{mso-style-priority:9;
mso-style-link:"Überschrift 3 Zchn";
mso-margin-top-alt:auto;
margin-right:0cm;
mso-margin-bottom-alt:auto;
margin-left:0cm;
font-size:13.5pt;
font-family:"Times New Roman",serif;
font-weight:bold;}
a:link, span.MsoHyperlink
{mso-style-priority:99;
color:#0563C1;
text-decoration:underline;}
a:visited, span.MsoHyperlinkFollowed
{mso-style-priority:99;
color:#954F72;
text-decoration:underline;}
p
{mso-style-priority:99;
mso-margin-top-alt:auto;
margin-right:0cm;
mso-margin-bottom-alt:auto;
margin-left:0cm;
font-size:12.0pt;
font-family:"Times New Roman",serif;}
span.E-MailFormatvorlage17
{mso-style-type:personal-compose;
font-family:"Calibri",sans-serif;
color:windowtext;}
span.berschrift3Zchn
{mso-style-name:"Überschrift 3 Zchn";
mso-style-priority:9;
mso-style-link:"Überschrift 3";
font-family:"Times New Roman",serif;
mso-fareast-language:DE;
font-weight:bold;}
.MsoChpDefault
{mso-style-type:export-only;
font-family:"Calibri",sans-serif;
mso-fareast-language:EN-US;}
@page WordSection1
{size:612.0pt 792.0pt;
margin:70.85pt 70.85pt 2.0cm 70.85pt;}
div.WordSection1
{page:WordSection1;}
/* List Definitions */
@list l0
{mso-list-id:289630252;
mso-list-template-ids:1262813098;}
@list l0:level1
{mso-level-number-format:bullet;
mso-level-text:\F0B7;
mso-level-tab-stop:36.0pt;
mso-level-number-position:left;
text-indent:-18.0pt;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l0:level2
{mso-level-number-format:bullet;
mso-level-text:o;
mso-level-tab-stop:72.0pt;
mso-level-number-position:left;
text-indent:-18.0pt;
mso-ansi-font-size:10.0pt;
font-family:"Courier New";
mso-bidi-font-family:"Times New Roman";}
@list l0:level3
{mso-level-number-format:bullet;
mso-level-text:\F0A7;
mso-level-tab-stop:108.0pt;
mso-level-number-position:left;
text-indent:-18.0pt;
mso-ansi-font-size:10.0pt;
font-family:Wingdings;}
@list l0:level4
{mso-level-number-format:bullet;
mso-level-text:\F0A7;
mso-level-tab-stop:144.0pt;
mso-level-number-position:left;
text-indent:-18.0pt;
mso-ansi-font-size:10.0pt;
font-family:Wingdings;}
@list l0:level5
{mso-level-number-format:bullet;
mso-level-text:\F0A7;
mso-level-tab-stop:180.0pt;
mso-level-number-position:left;
text-indent:-18.0pt;
mso-ansi-font-size:10.0pt;
font-family:Wingdings;}
@list l0:level6
{mso-level-number-format:bullet;
mso-level-text:\F0A7;
mso-level-tab-stop:216.0pt;
mso-level-number-position:left;
text-indent:-18.0pt;
mso-ansi-font-size:10.0pt;
font-family:Wingdings;}
@list l0:level7
{mso-level-number-format:bullet;
mso-level-text:\F0A7;
mso-level-tab-stop:252.0pt;
mso-level-number-position:left;
text-indent:-18.0pt;
mso-ansi-font-size:10.0pt;
font-family:Wingdings;}
@list l0:level8
{mso-level-number-format:bullet;
mso-level-text:\F0A7;
mso-level-tab-stop:288.0pt;
mso-level-number-position:left;
text-indent:-18.0pt;
mso-ansi-font-size:10.0pt;
font-family:Wingdings;}
@list l0:level9
{mso-level-number-format:bullet;
mso-level-text:\F0A7;
mso-level-tab-stop:324.0pt;
mso-level-number-position:left;
text-indent:-18.0pt;
mso-ansi-font-size:10.0pt;
font-family:Wingdings;}
ol
{margin-bottom:0cm;}
ul
{margin-bottom:0cm;}
--></style><!--[if gte mso 9]><xml>
<o:shapedefaults v:ext="edit" spidmax="1026" />
</xml><![endif]--><!--[if gte mso 9]><xml>
<o:shapelayout v:ext="edit">
<o:idmap v:ext="edit" data="1" />
</o:shapelayout></xml><![endif]-->
</head>
<body lang="DE" link="#0563C1" vlink="#954F72">
<div class="WordSection1">
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><span style="font-size:13.5pt;font-family:"Times New Roman",serif;mso-fareast-language:DE">Masterarbeit zum Thema "Wireless Cooperation for Deep Learning"<o:p></o:p></span></b></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-language:DE">Link zur Ausschreibung (DE):
</span><span lang="EN-US" style="font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-language:DE"><a href="https://recruiting.fraunhofer.de/Vacancies/32309/Description/1"><span lang="DE">https://recruiting.fraunhofer.de/Vacancies/32309/Description/1</span></a></span><span lang="EN-US" style="font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-language:DE">
</span><span style="font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-language:DE"><br>
Link zur Ausschreibung (EN): <a href="https://recruiting.fraunhofer.de/Vacancies/32309/Description/2">
https://recruiting.fraunhofer.de/Vacancies/32309/Description/2</a> </span><b><span style="font-size:13.5pt;font-family:"Times New Roman",serif;mso-fareast-language:DE"><o:p></o:p></span></b></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-language:DE">Die Abteilung „Wireless Communications and Networks“ des Fraunhofer Institut für Nachrichtentechnik,
Heinrich-Hertz-Institut, entwickelt zukünftige, drahtlose Kommunikationssysteme. Die Arbeitsgruppe " Signal+Information Processing" arbeitet im internationalen Umfeld in Forschungsprojekten zu hochaktuellen Fragestellungen im Bereich des Mobilfunks.
<o:p></o:p></span></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><span style="font-size:13.5pt;font-family:"Times New Roman",serif;mso-fareast-language:DE">Was Sie mitbringen<o:p></o:p></span></b></p>
<ul type="disc">
<li class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo1">
<span style="font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-language:DE">Studierende (Master/Diplom) der Fachrichtungen Elektrotechnik, Informatik, Mathematik, oder ähnlicher Studienrichtungen, mit Schwerpunkt auf Kommunikation und/oder maschinellem
Lernen<o:p></o:p></span></li><li class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo1">
<span style="font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-language:DE">Gute Programmierkenntnisse in Python und/oder MATLAB<o:p></o:p></span></li><li class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo1">
<span style="font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-language:DE">Sehr gute Kenntnisse in Signalverarbeitung und maschinellem Lernen<o:p></o:p></span></li><li class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo1">
<span style="font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-language:DE">Erfahrung mit eingebetteter Hardware und/oder GPU Programmierung ist von Vorteil<o:p></o:p></span></li></ul>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><span style="font-size:13.5pt;font-family:"Times New Roman",serif;mso-fareast-language:DE">Was Sie erwarten können<o:p></o:p></span></b></p>
<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-language:DE">Die Masterarbeit besteht aus zwei Phasen:<br>
1. Ausgehend von einer existierenden Testumgebung aus mit Kameras ausgestatteten eingebetteten Computern (NVIDIA Jetson Architektur) soll in der ersten Phase ein individuelles Bildklassifizierungssystem mittels state-of-the-art Klassifizierungsmethoden (z.B.
basierend auf Caffe/Tensorflow und AlexNet) aufgebaut werden. <br>
2. In der zweiten Phase sollen die individuellen Entscheidungen zusammengeführt werden, um die Klassifizierungsgenauigkeit zu erhöhen. Dabei sollen die Knoten Wifi/Bluetooth basierte Kommunikationsprotokolle nutzen um Informationen über ihre lokalen Entscheidungen
auszutauschen. Ein wesentliches Ziel ist dabei den Umfang der übertragenen Daten mittels neuartiger Consensus-Algorithmen sowie Methoden der konvexen Optimierung zu reduzieren und gleichzeitig eine hohe Klassifizierungsgenauigkeit aufrecht zu erhalten.
<o:p></o:p></span></p>
<p><strong>Fragen zu dieser Position beantwortet Ihnen:</strong><br>
Herr Dr. Martin Kasparick<br>
Tel: +49 3031002 853<br>
E-Mail: <a href="mailto:martin.kasparick@hhi.fraunhofer.de">martin.kasparick@hhi.fraunhofer.de</a><o:p></o:p></p>
<p class="MsoNormal"><a href="http://www.hhi.fraunhofer.de">http://www.hhi.fraunhofer.de</a><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
</div>
</body>
</html>