<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
</head>
<body>
格浴浸湬㩳㵶產湲猺档浥獡洭捩潲潳瑦挭浯瘺汭•浸湬㩳㵯產湲猺档浥獡洭捩潲潳瑦挭浯漺晦捩㩥景楦散•浸湬㩳㵷產湲猺档浥獡洭捩潲潳瑦挭浯漺晦捩㩥潷摲•浸湬㩳㵭栢瑴㩰⼯捳敨慭業牣獯景潣⽭景楦散㈯〰⼴㈱漯浭≬砠汭獮∽瑨灴⼺眯睷眮⸳牯⽧剔刯䍅栭浴㑬∰㰾敨摡㰾敭慴栠瑴⵰煥極㵶潃瑮湥祔数挠湯整瑮∽整瑸栯浴㭬挠慨獲瑥甽獡楣≩㰾敭慴渠浡㵥敇敮慲潴潣瑮湥㵴䴢捩潲潳瑦圠牯㔱⠠楦瑬牥摥洠摥畩⥭㸢猼祴敬㰾ⴡഭ⼊潆瑮䐠晥湩瑩潩獮⨠യ䀊潦瑮昭捡ऊ晻湯慦業祬场湩摧湩獧഻ऊ慰潮敳ㄭ㔺〠〠〠〠〠〠〠〠〠紻晀湯慦散笉潦瑮昭浡汩㩹䌢浡牢慩䴠瑡≨഻ऊ慰潮敳ㄭ㈺㐠㔠㌠㔠㐠㘠㌠㈠㐠紻晀湯慦散笉潦瑮昭浡汩㩹慃楬牢㭩瀉湡獯ⵥ㨱′㔱㔠㈠㈠㈠㐠㌠㈠㐠紻⨯匠祴敬䐠晥湩瑩潩獮⨠യ瀊䴮潳潎浲污楬䴮潳潎浲污楤獍乯牯慭൬ऊ浻牡楧㩮挰㭭洉牡楧潢瑴浯⸺〰瑰഻ऊ潦瑮猭穩㩥ㄱ〮瑰഻ऊ潦瑮昭浡汩㩹䌢污扩楲Ⱒ慳獮猭牥晩紻㩡楬歮灳湡䴮潳祈数汲湩൫ऊ浻潳猭祴敬瀭楲牯瑩㩹㤹഻ऊ潣潬㩲〣㘵䌳㬱琉硥敤潣慲楴湯町摮牥楬敮紻㩡楶楳整Ɽ猠慰獍䡯灹牥楬歮潆汬睯摥笉獭ⵯ瑳汹ⵥ牰潩楲祴㤺㬹按汯牯⌺㔹䘴㈷഻ऊ整瑸搭捥牯瑡潩㩮湵敤汲湩㭥ൽ瀊䴮潳楌瑳慐慲牧灡ⱨ氠獍䱯獩側牡条慲桰楤獍䱯獩側牡条慲桰笉獭ⵯ瑳汹ⵥ牰潩楲祴㌺㬴洉牡楧潴㩰挰㭭洉牡楧楲桧㩴挰㭭洉牡楧潢瑴浯㠺〮瑰഻ऊ慭杲湩氭晥㩴㘳〮瑰഻ऊ獭ⵯ摡ⵤ灳捡㩥畡潴഻ऊ楬敮栭楥桧㩴〱┵഻ऊ潦瑮猭穩㩥ㄱ〮瑰഻ऊ潦瑮昭浡汩㩹䌢污扩楲Ⱒ慳獮猭牥晩紻獍䱯獩側牡条慲桰硃灓楆獲ⱴ氠獍䱯獩側牡条慲桰硃灓楆獲ⱴ搠癩䴮潳楌瑳慐慲牧灡䍨卸䙰物瑳笉獭ⵯ瑳汹ⵥ牰潩楲祴㌺㬴洉潳猭祴敬琭灹㩥硥潰瑲漭汮㭹洉牡楧潴㩰挰㭭洉牡楧楲桧㩴挰㭭洉牡楧潢瑴浯〺浣഻ऊ慭杲湩氭晥㩴㘳〮瑰഻ऊ慭杲湩戭瑯潴㩭〮〰瀱㭴洉潳愭摤猭慰散愺瑵㭯氉湩ⵥ敨杩瑨ㄺ㔰㬥昉湯楳敺ㄺ⸱瀰㭴昉湯慦業祬∺慃楬牢≩猬湡敳楲㭦ൽ瀊䴮潳楌瑳慐慲牧灡䍨卸䵰摩汤ⱥ氠獍䱯獩側牡条慲桰硃灓楍摤敬楤獍䱯獩側牡条慲桰硃灓楍摤敬笉獭ⵯ瑳汹ⵥ牰潩楲祴㌺㬴洉潳猭祴敬琭灹㩥硥潰瑲漭汮㭹洉牡楧潴㩰挰㭭洉牡楧楲桧㩴挰㭭洉牡楧潢瑴浯〺浣഻ऊ慭杲湩氭晥㩴㘳〮瑰഻ऊ慭杲湩戭瑯潴㩭〮〰瀱㭴洉潳愭摤猭慰散愺瑵㭯氉湩ⵥ敨杩瑨ㄺ㔰㬥昉湯楳敺ㄺ⸱瀰㭴昉湯慦業祬∺慃楬牢≩猬湡敳楲㭦ൽ瀊䴮潳楌瑳慐慲牧灡䍨卸䱰獡ⱴ氠獍䱯獩側牡条慲桰硃灓慌瑳楤獍䱯獩側牡条慲桰硃灓慌瑳笉獭ⵯ瑳汹ⵥ牰潩楲祴㌺㬴洉潳猭祴敬琭灹㩥硥潰瑲漭汮㭹洉牡楧潴㩰挰㭭洉牡楧楲桧㩴挰㭭洉牡楧潢瑴浯㠺〮瑰഻ऊ慭杲湩氭晥㩴㘳〮瑰഻ऊ獭ⵯ摡ⵤ灳捡㩥畡潴഻ऊ楬敮栭楥桧㩴〱┵഻ऊ潦瑮猭穩㩥ㄱ〮瑰഻ऊ潦瑮昭浡汩㩹䌢污扩楲Ⱒ慳獮猭牥晩紻獭湯牯慭ぬ楬洮潳潮浲污ⰰ搠癩洮潳潮浲污രऊ浻潳猭祴敬渭浡㩥獭湯牯慭㭬洉潳洭牡楧潴⵰污㩴畡潴഻ऊ慭杲湩爭杩瑨〺浣഻ऊ獭ⵯ慭杲湩戭瑯潴污㩴畡潴഻ऊ慭杲湩氭晥㩴挰㭭昉湯楳敺ㄺ⸲瀰㭴昉湯慦業祬∺楔敭敎⁷潒慭≮猬牥晩紻灳湡䔮慭汩瑓汹ㅥഹऊ浻潳猭祴敬琭灹㩥数獲湯污挭浯潰敳഻ऊ潦瑮昭浡汩㩹䌢污扩楲Ⱒ慳獮猭牥晩഻ऊ潣潬㩲楷摮睯整瑸紻䴮潳桃䑰晥畡瑬笉獭ⵯ瑳汹ⵥ祴数攺灸牯湯祬഻ऊ潦瑮猭穩㩥〱〮瑰紻灀条潗摲敓瑣潩ㅮ笉楳敺㘺㈱〮瑰㜠㈹〮瑰഻ऊ慭杲湩㜺⸰㔸瑰㜠⸰㔸瑰㜠⸰㔸瑰㜠⸰㔸瑰紻楤潗摲敓瑣潩ㅮ笉慰敧场牯卤捥楴湯㬱ൽ⼊楌瑳䐠晥湩瑩潩獮⨠യ䀊楬瑳氠രऊ浻潳氭獩摩㠺㤰㘸㠰㔹഻ऊ獭ⵯ楬瑳琭灹㩥票牢摩഻ऊ獭ⵯ楬瑳琭浥汰瑡ⵥ摩㩳㌱ㄷ㐰㐳㠹㈠㤶㈲㠱㤸㘠㘷㠹ㄷ″㜶㤶㜸㔱㘠㘷㠹〷″㜶㤶㜸㌱㘠㘷㠹ㄷ‵㜶㤶㜸㌰㘠㘷㠹ㄷ″㜶㤶㜸㔱紻汀獩⁴ぬ氺癥汥റऊ浻潳氭癥汥渭浵敢潦浲瑡戺汵敬㭴洉潳氭癥汥琭硥㩴䙜䈰㬷洉潳氭癥汥琭扡猭潴㩰潮敮഻ऊ獭ⵯ敬敶畮扭牥瀭獯瑩潩㩮敬瑦഻ऊ整瑸椭摮湥㩴ㄭ⸸瀰㭴昉湯慦業祬区浹潢㭬ൽ䀊楬瑳氠㨰敬敶㉬笉獭ⵯ敬敶畮扭牥昭牯慭㩴污桰ⵡ潬敷㭲洉潳氭癥汥琭扡猭潴㩰潮敮഻ऊ獭ⵯ敬敶畮扭牥瀭獯瑩潩㩮敬瑦഻ऊ整瑸椭摮湥㩴ㄭ⸸瀰㭴ൽ䀊楬瑳氠㨰敬敶㍬笉獭ⵯ敬敶畮扭牥昭牯慭㩴潲慭潬敷㭲洉潳氭癥汥琭扡猭潴㩰潮敮഻ऊ獭ⵯ敬敶畮扭牥瀭獯瑩潩㩮楲桧㭴琉硥湩敤瑮ⴺ⸹瀰㭴ൽ䀊楬瑳氠㨰敬敶㑬笉獭ⵯ敬敶慴ⵢ瑳灯渺湯㭥洉潳氭癥汥渭浵敢潰楳楴湯氺晥㭴琉硥湩敤瑮ⴺ㠱〮瑰紻汀獩⁴ぬ氺癥汥വऊ浻潳氭癥汥渭浵敢潦浲瑡愺灬慨氭睯牥഻ऊ獭ⵯ敬敶慴ⵢ瑳灯渺湯㭥洉潳氭癥汥渭浵敢潰楳楴湯氺晥㭴琉硥湩敤瑮ⴺ㠱〮瑰紻汀獩⁴ぬ氺癥汥ശऊ浻潳氭癥汥渭浵敢潦浲瑡爺浯湡氭睯牥഻ऊ獭ⵯ敬敶慴ⵢ瑳灯渺湯㭥洉潳氭癥汥渭浵敢潰楳楴湯爺杩瑨഻ऊ整瑸椭摮湥㩴㤭〮瑰紻汀獩⁴ぬ氺癥汥ഷऊ浻潳氭癥汥琭扡猭潴㩰潮敮഻ऊ獭ⵯ敬敶畮扭牥瀭獯瑩潩㩮敬瑦഻ऊ整瑸椭摮湥㩴ㄭ⸸瀰㭴ൽ䀊楬瑳氠㨰敬敶㡬笉獭ⵯ敬敶畮扭牥昭牯慭㩴污桰ⵡ潬敷㭲洉潳氭癥汥琭扡猭潴㩰潮敮഻
mso-level-number-position:left; text-indent:-18.0pt;} @list l0:level9 {mso-level-number-format:roman-lower; mso-level-tab-stop:none; mso-level-number-position:right; text-indent:-9.0pt;} @list l1 {mso-list-id:1091468200; mso-list-type:hybrid; mso-list-template-ids:1280710644
269221889 67698691 67698693 67698689 67698691 67698693 67698689 67698691 67698693;} @list l1:level1 {mso-level-number-format:bullet; mso-level-text:\F0B7; mso-level-tab-stop:none; mso-level-number-position:left; margin-left:38.5pt; text-indent:-18.0pt; font-family:Symbol;}
@list l1:level2 {mso-level-number-format:bullet; mso-level-text:o; mso-level-tab-stop:none; mso-level-number-position:left; margin-left:74.5pt; text-indent:-18.0pt; font-family:"Courier New";} @list l1:level3 {mso-level-number-format:bullet; mso-level-text:\F0A7;
mso-level-tab-stop:none; mso-level-number-position:left; margin-left:110.5pt; text-indent:-18.0pt; font-family:Wingdings;} @list l1:level4 {mso-level-number-format:bullet; mso-level-text:\F0B7; mso-level-tab-stop:none; mso-level-number-position:left; margin-left:146.5pt;
text-indent:-18.0pt; font-family:Symbol;} @list l1:level5 {mso-level-number-format:bullet; mso-level-text:o; mso-level-tab-stop:none; mso-level-number-position:left; margin-left:182.5pt; text-indent:-18.0pt; font-family:"Courier New";} @list l1:level6 {mso-level-number-format:bullet;
mso-level-text:\F0A7; mso-level-tab-stop:none; mso-level-number-position:left; margin-left:218.5pt; text-indent:-18.0pt; font-family:Wingdings;} @list l1:level7 {mso-level-number-format:bullet; mso-level-text:\F0B7; mso-level-tab-stop:none; mso-level-number-position:left;
margin-left:254.5pt; text-indent:-18.0pt; font-family:Symbol;} @list l1:level8 {mso-level-number-format:bullet; mso-level-text:o; mso-level-tab-stop:none; mso-level-number-position:left; margin-left:290.5pt; text-indent:-18.0pt; font-family:"Courier New";}
@list l1:level9 {mso-level-number-format:bullet; mso-level-text:\F0A7; mso-level-tab-stop:none; mso-level-number-position:left; margin-left:326.5pt; text-indent:-18.0pt; font-family:Wingdings;} ol {margin-bottom:0cm;} ul {margin-bottom:0cm;} --><!--[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]-->
<div class="WordSection1">
<p class="MsoNormal"><b><span lang="EN-GB" style="font-size:14.0pt">Postdoc position in the lab of Prof. Gregoire Courtine at EPFL (Lausanne, Switzerland)<o:p></o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-GB"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-GB">Machine learning techniques to develop and enhance clinical treatments based on electrical stimulation of the spinal cord
<o:p></o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-GB"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-GB">Location:<o:p></o:p></span></b></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-GB">The laboratory of Prof. Gregoire Courtine at the Swiss Federal Institute of Technology (EPFL) in Lausanne, Switzerland, is looking to fill a fully funded postdoc position. The qualified candidate
will benefit from joining a very dynamic and multidisciplinary group working at the interface of computational neuroscience, neuroengineering, prosthetics and biology. EPFL provides state-of-the-art facilities and is one of the leading technical universities
worldwide. Postdoc salaries at EPFL rank the highest in the world.<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Opportunity:<o:p></o:p></span></b></p>
<p class="MsoNormal">The offered position will be based at the Defitech Center for interventional Neurotherapies (NeuroRestore) - a research and innovation center joining EPFL’s lab of Prof. Gregoire Courtine and the University Hospital of Lausanne (CHUV) lab
of Prof. Jocelyne Bloch. NeuroRestore conceives, develops and applies medical therapies aimed to restore neurological functions. To this end, NeuroRestore integrates implantable neurotechnologies with innovative treatments developed through rigorous preclinical
and clinical studies. By working with our network of vibrant high-tech start-ups and established medical technology companies, NeuroRestore is committed to validate our medical therapy concepts. The overarching goal of NeuroRestore is to see our medical therapies
used every day in hospitals and rehabilitation clinics worldwide.<o:p></o:p></p>
<p class="MsoNormal"><b><span lang="EN-GB"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-GB">Description:<o:p></o:p></span></b></p>
<p class="MsoNormal" style="margin-bottom:3.0pt;text-align:justify">Therapies based on epidural electrical stimulation (EES) of the spinal cord can restore the ability to walk to people paralyzed by spinal cord injury, and alleviate gait deficits of people
with Parkinson’s disease. EES does this by recruiting sensory axons within dorsal spinal roots that enter the spinal cord between the vertebrae to increase the activation of the spinal motor pools that, in turn, move the muscles. Yet, the efficacy of the EES-based
therapies relies on synchronizing users’ movement intentions with the spatiotemporal stimulation protocols that reliably and accurately generate paralyzed movements. Due to the large state space of all the stimulation parameters (location, amplitude, frequency,
etc.) efficacy of the therapy depends on the fast and accurate initialization of the stimulation protocols. As the patients use the stimulation, small movements of the array, as well as changes in spine position due to users’ posture can reduce the usability
of the stimulation. Stimulation efficacy can be enhanced by dynamically adjusting the stimulation protocols to changes to the way how to users’ spinal cord reacts to stimulation. Finally, the functional use of the stimulation largely depends on the accurate
timing of stimulation delivery. Machine learning approaches that infer users’ intentions based on behavioral, physiological or neural recordings can vastly improve the synchronization between intended and therapy-supported movements and, therefore, play a
critical role in achieving functional recovery of patients. While the current medical devices mostly support block-based stimulation protocols that remain constant for hundreds of milliseconds, upcoming devices will enable changes of stimulation at a millisecond
resolution, thus opening a new field for machine learning approaches that exploit these capabilities.<b><o:p></o:p></b></p>
<p class="MsoNormal" style="mso-margin-top-alt:6.0pt;margin-right:0cm;margin-bottom:3.0pt;margin-left:0cm;text-align:justify">
The successful candidate will work to develop, implement and apply machine learning algorithms and approaches to enhance EES-based therapies. Specifically, he will:<b><o:p></o:p></b></p>
<ul style="margin-top:0cm" type="disc">
<li class="MsoListParagraphCxSpFirst" style="margin-top:6.0pt;margin-bottom:3.0pt;margin-left:0cm;mso-add-space:auto;text-align:justify;line-height:14.0pt;mso-list:l0 level1 lfo2">
Design the mapping procedures for the generation of transfer functions that relate the continuously-controlled stimulation to the evoked muscle activity.<b><o:p></o:p></b></li><li class="MsoListParagraphCxSpMiddle" style="margin-top:6.0pt;margin-bottom:3.0pt;margin-left:0cm;mso-add-space:auto;text-align:justify;line-height:14.0pt;mso-list:l0 level1 lfo2">
Develop algorithms that automatically adjust these transfer functions as the interaction between patients and their EES-based therapy evolves.<b><o:p></o:p></b></li><li class="MsoListParagraphCxSpMiddle" style="margin-top:6.0pt;margin-bottom:3.0pt;margin-left:0cm;mso-add-space:auto;text-align:justify;line-height:14.0pt;mso-list:l0 level1 lfo2">
Implement machine learning techniques that utilize users’ behavioral, physiological and neural signals to continuously synchronize the delivery of stimulation with the users’ movement intentions.<b><o:p></o:p></b></li><li class="MsoListParagraphCxSpMiddle" style="margin-top:6.0pt;margin-bottom:3.0pt;margin-left:0cm;mso-add-space:auto;text-align:justify;line-height:14.0pt;mso-list:l0 level1 lfo2">
Lead the team that develops machine learning methods to initialize and adjust block-based EES protocols.<b><o:p></o:p></b></li><li class="MsoListParagraphCxSpLast" style="margin-top:6.0pt;margin-bottom:3.0pt;margin-left:0cm;mso-add-space:auto;text-align:justify;line-height:14.0pt;mso-list:l0 level1 lfo2">
Assist and oversee the development and implementation of machine learning methods that use inference of discrete motor events to synchronize block-based EES protocols with the users’ intentions.<b><o:p></o:p></b></li></ul>
<p class="MsoNormal" style="mso-margin-bottom-alt:auto;text-align:justify;background:white">
By integrating well-equipped and expertly staffed rodent, non-human primate and clinical research facilities, NeuroRestore provides an ideal substrate for rapidly developing, integrating and clinically validating cutting-edge machine learning concepts within
medical therapies, with the capacity to push successfully proven concepts into the technology transition phase. The successful candidate will have access to these animal platforms and will work within the framework of multiple NeuroRestore clinical trials
with people with spinal cord injury and Parkinson’s disease. They will benefit from the possibility of validating their concepts in animal experiments and implementing them within the therapies being tested in the clinical trials.<span style="color:#212121"><o:p></o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Prerequisites:<o:p></o:p></span></b></p>
<ul style="margin-top:0cm" type="disc">
<li class="MsoListParagraphCxSpFirst" style="margin-left:2.5pt;mso-add-space:auto;mso-list:l1 level1 lfo4">
Doctoral degree (PhD)<o:p></o:p></li><li class="MsoListParagraphCxSpMiddle" style="margin-left:2.5pt;mso-add-space:auto;mso-list:l1 level1 lfo4">
Proficiency in Python, Matlab and C++<o:p></o:p></li><li class="MsoListParagraphCxSpMiddle" style="margin-left:2.5pt;mso-add-space:auto;mso-list:l1 level1 lfo4">
Strong background in quantitative data analysis<o:p></o:p></li><li class="MsoListParagraphCxSpMiddle" style="margin-left:2.5pt;mso-add-space:auto;mso-list:l1 level1 lfo4">
Experience with applying multiple machine learning techniques to behavioral, physiological, biological and/or neural datasets<o:p></o:p></li><li class="MsoListParagraphCxSpLast" style="margin-left:2.5pt;mso-add-space:auto;mso-list:l1 level1 lfo4">
Good written and verbal skills in English<o:p></o:p></li></ul>
<p class="MsoNormal"><b><span lang="EN-GB">Contact:<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-GB">Applications including a CV and a cover letter describing
</span>your background and interest <span lang="EN-GB">should be sent to <a href="mailto:tomislav.milekovic@epfl.ch">
tomislav.milekovic@epfl.ch</a>. Informal inquiries are welcome.<o:p></o:p></span></p>
</div>
</body>
</html>