{"id":40415,"date":"2025-05-06T11:19:26","date_gmt":"2025-05-06T09:19:26","guid":{"rendered":"https:\/\/xitaso.com\/?page_id=40415"},"modified":"2026-06-02T14:26:39","modified_gmt":"2026-06-02T12:26:39","slug":"mawis-ki","status":"publish","type":"page","link":"https:\/\/xitaso.com\/es\/proyectos\/mawis-ki\/","title":{"rendered":"MaWis-KI: Previsi\u00f3n de la vida \u00fatil de la tecnolog\u00eda electr\u00f3nica de gama alta"},"content":{"rendered":"

[vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbfull_width\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb z_index=\u00bb\u00bb el_class=\u00bbheader_level2_container\u00bb][vc_column][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbfull_width\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb css=\u00bb.vc_custom_1720518350293{background-image: url(https:\/\/xitaso.com\/wp-content\/uploads\/Header-Lebensdauerprognose-Elektronik.jpg?id=40696) !important;}\u00bb][vc_column_inner offset=\u00bbvc_hidden-xs\u00bb][vc_empty_space height=\u00bb500″][\/vc_column_inner][\/vc_row_inner][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbfull_width\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner offset=\u00bbvc_hidden-lg vc_hidden-md vc_hidden-sm\u00bb][vc_single_image image=\u00bb38832″ img_size=\u00bbfull\u00bb css=\u00bb\u00bb qode_css_animation=\u00bb\u00bb][\/vc_column_inner][\/vc_row_inner][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbgrid\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner][vc_raw_html css=\u00bb\u00bb]JTNDZGl2JTIwY2xhc3MlM0QlMjJoZWFkZXJfbGV2ZWwyJTIyJTNFJTBBJTNDZGl2JTIwY2xhc3MlM0QlMjJ0b3BwZXIlMjIlM0VJQSUyMHklMjBvcHRpbWl6YWNpJUMzJUIzbiUzQyUyRmRpdiUzRSUwQSUzQ2gxJTNFUHJldmlzaSVDMyVCM24lMjBkZSUyMGxhJTIwdmlkYSUyMCVDMyVCQXRpbCUyMGRlJTIwbGElMjB0ZWNub2xvZyVDMyVBRGElMjBlbGVjdHIlQzMlQjNuaWNhJTIwZGUlMjBnYW1hJTIwYWx0YSUzQyUyRmgxJTNFJTBBJTNDJTJGZGl2JTNFJTBBJTBB[\/vc_raw_html][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbfull_width\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb css=\u00bb.vc_custom_1720175303281{background-color: #e8e0e0 !important;}\u00bb z_index=\u00bb\u00bb][vc_column][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbgrid\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner width=\u00bb1\/2″][vc_empty_space height=\u00bb60″][vc_column_text css=\u00bb\u00bb]<\/p>\n

El reto<\/h2>\n

Los coches modernos son cada vez m\u00e1s aut\u00f3nomos y dependen de un gran n\u00famero de m\u00f3dulos electr\u00f3nicos, como sensores y unidades de control. Deben funcionar de forma fiable durante muchos a\u00f1os en condiciones extremas como el fr\u00edo, la nieve, la lluvia o el calor. La calidad de las uniones soldadas desempe\u00f1a un papel fundamental, ya que conectan los componentes mec\u00e1nica y el\u00e9ctricamente. Sin embargo, bajo tensi\u00f3n termomec\u00e1nica, existe el riesgo de que fallen las uniones soldadas y, por consiguiente, todo el m\u00f3dulo.[\/vc_column_text][vc_empty_space height=\u00bb30″][vc_empty_space height=\u00bb30″ el_class=\u00bbausgeblendet\u00bb][\/vc_column_inner][vc_column_inner width=\u00bb1\/2″][vc_empty_space height=\u00bb30″ el_class=\u00bbnot-on-mobile\u00bb][vc_empty_space height=\u00bb30″][vc_column_text css=\u00bb\u00bb]<\/p>\n

Nuestra aportaci\u00f3n<\/h2>\n

Como parte del proyecto de investigaci\u00f3n MaWis-KI, XITASO est\u00e1 trabajando con los colaboradores del proyecto para investigar y desarrollar enfoques innovadores de IA y aprendizaje profundo (deep learning<\/em>) que puedan evaluar eficazmente la idoneidad de los materiales de soldadura para cada aplicaci\u00f3n en la fase de desarrollo temprana de m\u00f3dulos el\u00e9ctricos. El objetivo de la investigaci\u00f3n es crear m\u00f3dulos electr\u00f3nicos altamente fiables con una inversi\u00f3n m\u00ednima de tiempo y con un coste reducido.[\/vc_column_text][vc_empty_space height=\u00bb30″][\/vc_column_inner][\/vc_row_inner][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbgrid\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner][vc_column_text css=\u00bb\u00bb]<\/p>\n

Tecnolog\u00edas<\/h2>\n

[\/vc_column_text][vc_empty_space height=\u00bb15″][vc_raw_html]JTNDc3BhbiUyMGNsYXNzJTNEJTIydGVjaG5vbG9naWVuJTIyJTNFTWFjaGluZSUyMExlYXJuaW5nJTNDJTJGc3BhbiUzRSUwQSUzQ3NwYW4lMjBjbGFzcyUzRCUyMnRlY2hub2xvZ2llbiUyMiUzRVJlcHJlc2VudGF0aW9uJTIwTGVhcm5pbmclM0MlMkZzcGFuJTNFJTBBJTNDc3BhbiUyMGNsYXNzJTNEJTIydGVjaG5vbG9naWVuJTIyJTNFTmV1cmFsJTIwT0RFcyUzQyUyRnNwYW4lM0UlMEElM0NzcGFuJTIwY2xhc3MlM0QlMjJ0ZWNobm9sb2dpZW4lMjIlM0VUaW1lJTIwU2VyaWVzJTNDJTJGc3BhbiUzRQ==[\/vc_raw_html][vc_empty_space height=\u00bb60″][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbgrid\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb z_index=\u00bb\u00bb][vc_column][vc_empty_space height=\u00bb30″ el_class=\u00bbnot-on-mobile\u00bb][vc_empty_space height=\u00bb50″][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbfull_width\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb el_class=\u00bbtwo-column-with-heading-on-top\u00bb z_index=\u00bb\u00bb][vc_column][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbgrid\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner width=\u00bb1\/2″][vc_column_text css=\u00bb\u00bb]<\/p>\n

Aprendizaje profundo y el problema de la escasez de datos<\/h2>\n

[\/vc_column_text][\/vc_column_inner][vc_column_inner width=\u00bb1\/2″][\/vc_column_inner][\/vc_row_inner][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbgrid\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner width=\u00bb1\/2″][vc_column_text css=\u00bb\u00bb]El aprendizaje profundo permite aprender la representaci\u00f3n de los datos en varias capas de abstracci\u00f3n y utilizarla para mucho m\u00e1s que la clasificaci\u00f3n o la regresi\u00f3n. Estos m\u00e9todos han redefinido el estado de la t\u00e9cnica en muchos \u00e1mbitos, como la visi\u00f3n artificial (computer vision<\/em>) o el procesamiento del lenguaje natural (natural language processing<\/em>). El aprendizaje profundo, que se basa en redes neuronales, requiere una gran cantidad de datos como base para el aprendizaje de las representaciones, ya que el espacio muestral de los par\u00e1metros que se pueden aprender es altamente dimensional. Sin embargo, la creaci\u00f3n de grandes conjuntos de datos en la ciencia de los materiales es dif\u00edcil, puesto que precisa un gran n\u00famero de muestras y experimentos complejos. En consecuencia, aprender redes neuronales precisas y robustas a partir de peque\u00f1as cantidades de datos es muy dif\u00edcil.[\/vc_column_text][\/vc_column_inner][vc_column_inner width=\u00bb1\/2″][vc_column_text css=\u00bb\u00bb]Por lo tanto, el objetivo del proyecto MaWis-KI es desarrollar, implementar y probar nuevos enfoques de aprendizaje autom\u00e1tico para la predicci\u00f3n de la vida \u00fatil de las soldaduras de esta\u00f1o, plata, cobre y, posiblemente, otros componentes (soldaduras SAC o SAC+). Sin embargo, debido a que la cantidad de datos es tan reducida, no se pueden utilizar m\u00e9todos est\u00e1ndares de aprendizaje profundo. En su lugar, se est\u00e1n investigando m\u00e9todos de IA basados en modelos y conocimientos, como las ecuaciones diferenciales ordinarias neuronales (ODE neuronales), y se est\u00e1 evaluando su potencial como parte del proyecto de investigaci\u00f3n.[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbgrid\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb z_index=\u00bb\u00bb][vc_column][vc_empty_space height=\u00bb30″ el_class=\u00bbnot-on-mobile\u00bb][vc_empty_space height=\u00bb30″][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbfull_width\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb el_class=\u00bbtwo-column-with-heading-on-top\u00bb z_index=\u00bb\u00bb][vc_column][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbgrid\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner width=\u00bb1\/2″][vc_column_text css=\u00bb\u00bb]<\/p>\n

Aprendizaje contrastivo para aprender buenas representaciones<\/h3>\n

[\/vc_column_text][vc_empty_space height=\u00bb15px\u00bb][\/vc_column_inner][vc_column_inner width=\u00bb1\/2″][\/vc_column_inner][\/vc_row_inner][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbgrid\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner width=\u00bb1\/2″][vc_column_text css=\u00bb\u00bb]El aprendizaje contrastivo (contrastive learning<\/em>) es un m\u00e9todo de aprendizaje autom\u00e1tico cuyo objetivo es crear representaciones \u00fatiles de los datos. Funciona creando pares de puntos de datos que son similares o diferentes. Estos pares se colocan en un espacio de incrustaci\u00f3n con puntos de datos similares pr\u00f3ximos entre s\u00ed y puntos de datos diferentes alejados unos de otros.<\/p>\n

Mediante este proceso, el modelo aprende a extraer caracter\u00edsticas relevantes que hacen que los puntos de datos similares est\u00e9n cerca unos de otros en un espacio altamente dimensional y permite registrar informaci\u00f3n sem\u00e1ntica a partir de los datos. Como parte del proyecto, el aprendizaje contrastivo ha demostrado su utilidad para reconocer espec\u00edficamente grietas y defectos en im\u00e1genes de microscop\u00eda por ultrasonidos de juntas de soldadura.[\/vc_column_text][vc_empty_space height=\u00bb30px\u00bb][\/vc_column_inner][vc_column_inner width=\u00bb1\/2″][vc_single_image image=\u00bb42141″ img_size=\u00bblarge\u00bb add_caption=\u00bbyes\u00bb alignment=\u00bbcenter\u00bb css=\u00bb.vc_custom_1711016581099{margin-bottom: 5px !important;}\u00bb qode_css_animation=\u00bb\u00bb][vc_empty_space height=\u00bb15px\u00bb][vc_column_text css=\u00bb\u00bb]Mientras que el aprendizaje supervisado (supervised learning<\/em>) cl\u00e1sico consiste en una agrupaci\u00f3n seg\u00fan los tipos de componentes y soldaduras en el espacio de incrustaci\u00f3n, el aprendizaje contrastivo ordena los puntos de datos seg\u00fan el nivel de da\u00f1o en el espacio de incrustaci\u00f3n. De este modo, el modelo extrae las caracter\u00edsticas relevantes (representaci\u00f3n de la publicaci\u00f3n Contrastive pretraining of regression tasks in reliability forecasting of automotive electronics<\/em>).[\/vc_column_text][vc_empty_space height=\u00bb30px\u00bb][\/vc_column_inner][\/vc_row_inner][vc_empty_space height=\u00bb30″ el_class=\u00bbnot-on-mobile\u00bb][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbgrid\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb z_index=\u00bb\u00bb][vc_column][vc_empty_space height=\u00bb30″][vc_empty_space height=\u00bb50″][vc_column_text css=\u00bb\u00bb]<\/p>\n

Publicaciones sobre el proyecto de investigaci\u00f3n<\/h2>\n

[\/vc_column_text][vc_empty_space height=\u00bb15″][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbfull_width\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner width=\u00bb1\/6″][vc_empty_space height=\u00bb50px\u00bb][\/vc_column_inner][vc_column_inner width=\u00bb2\/3″][vc_raw_html css=\u00bb\u00bb]JTVCZG9jX2xpYnJhcnklMjBzb3J0X2J5JTNEJTIyZGF0ZSUyMiUyMGRvY190YWclM0QlMjJNYVdpcy1LSSUyMiUyMGRvY19jYXRlZ29yeSUzRCUyMnB1YmxpY2F0aW9uJTIyJTIwY29sdW1ucyUzRCUyMnRpdGxlJTJDZG9jX3RhZ3MlMkNkYXRlJTIyJTIwZGF0ZV9mb3JtYXQlM0QlMjJZJTIyJTVE[\/vc_raw_html][\/vc_column_inner][vc_column_inner width=\u00bb1\/6″][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbgrid\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb z_index=\u00bb\u00bb][vc_column][vc_empty_space height=\u00bb30″ el_class=\u00bbnot-on-mobile\u00bb][vc_empty_space height=\u00bb50″][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbfull_width\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb el_class=\u00bbtwo-column-with-heading-on-top\u00bb z_index=\u00bb\u00bb][vc_column][vc_empty_space height=\u00bb60px\u00bb][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbgrid\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner][vc_column_text css=\u00bb\u00bb]<\/p>\n

Participantes en el proyecto y financiaci\u00f3n<\/h2>\n

[\/vc_column_text][vc_empty_space height=\u00bb30px\u00bb][\/vc_column_inner][\/vc_row_inner][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbgrid\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner][vc_column_text css=\u00bb\u00bb]<\/p>\n

Colaboradores del proyecto<\/h3>\n

[\/vc_column_text][vc_empty_space height=\u00bb15px\u00bb][\/vc_column_inner][\/vc_row_inner][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbgrid\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner width=\u00bb1\/3″][vc_empty_space height=\u00bb15px\u00bb][vc_single_image image=\u00bb42972″ img_size=\u00bbfull\u00bb css=\u00bb.vc_custom_1713357745787{margin-top: 5px !important;margin-right: 5px !important;margin-bottom: 5px !important;margin-left: 5px !important;background-position: center !important;background-repeat: no-repeat !important;background-size: contain !important;}\u00bb qode_css_animation=\u00bb\u00bb][vc_empty_space height=\u00bb20px\u00bb][vc_column_text css=\u00bb\u00bb]Universidad T\u00e9cnica de Ingolstadt<\/strong>
\nLa Universidad T\u00e9cnica de Ingolstadt<\/a> ense\u00f1a e investiga en los campos de las ciencias el\u00e9ctricas y de la ingenier\u00eda, la inform\u00e1tica, la econom\u00eda, la sostenibilidad y las biociencias, y lo hace de forma innovadora y al d\u00eda de las nuevas tecnolog\u00edas.[\/vc_column_text][vc_empty_space height=\u00bb30px\u00bb][\/vc_column_inner][vc_column_inner width=\u00bb1\/3″][vc_empty_space height=\u00bb15px\u00bb][vc_single_image image=\u00bb42975″ img_size=\u00bbfull\u00bb css=\u00bb.vc_custom_1713357769824{margin-top: 5px !important;margin-right: 5px !important;margin-bottom: 5px !important;margin-left: 5px !important;background-position: center !important;background-repeat: no-repeat !important;background-size: contain !important;}\u00bb qode_css_animation=\u00bb\u00bb][vc_empty_space height=\u00bb25px\u00bb][vc_column_text css=\u00bb\u00bb]Conti Temic microelectronic GmbH<\/strong>
\nConti Temic microelectronic<\/a> desarrolla tecnolog\u00edas y servicios pioneros para la movilidad sostenible e interconectada de las personas y sus bienes.[\/vc_column_text][vc_empty_space height=\u00bb30px\u00bb][\/vc_column_inner][vc_column_inner width=\u00bb1\/3″][vc_empty_space height=\u00bb20px\u00bb][vc_single_image image=\u00bb42978″ img_size=\u00bbfull\u00bb css=\u00bb.vc_custom_1713357799997{margin-top: 5px !important;margin-right: 5px !important;margin-bottom: 5px !important;margin-left: 5px !important;background-position: center !important;background-repeat: no-repeat !important;background-size: contain !important;}\u00bb qode_css_animation=\u00bb\u00bb][vc_empty_space][vc_column_text css=\u00bb\u00bb]mts Consulting & Engineering <\/strong>GmbH<\/strong>
\nmts Consulting & Engineering<\/a> ayuda a empresas industriales con la implantaci\u00f3n met\u00f3dica y sostenible de productos robustos y procesos estables.[\/vc_column_text][vc_empty_space height=\u00bb30px\u00bb][\/vc_column_inner][\/vc_row_inner][vc_empty_space height=\u00bb10px\u00bb][vc_empty_space height=\u00bb40px\u00bb][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbfull_width\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb el_class=\u00bbtwo-column-with-heading-on-top\u00bb z_index=\u00bb\u00bb][vc_column][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbgrid\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner width=\u00bb1\/3″][vc_column_text css=\u00bb\u00bb]Patrocinador del proyecto[\/vc_column_text][vc_empty_space height=\u00bb15px\u00bb][vc_column_text css=\u00bb\u00bb]Ministerio de Econom\u00eda, Desarrollo Regional y Energ\u00eda de Baviera[\/vc_column_text][vc_empty_space height=\u00bb15″][vc_single_image image=\u00bb40723″ img_size=\u00bbfull\u00bb qode_css_animation=\u00bb\u00bb][\/vc_column_inner][vc_column_inner width=\u00bb1\/3″][vc_column_text css=\u00bb\u00bb]<\/p>\n

Programa de apoyo<\/h3>\n

[\/vc_column_text][vc_empty_space height=\u00bb15″][vc_column_text css=\u00bb\u00bb]L\u00ednea de ayudas para la digitalizaci\u00f3n (BayVFP)[\/vc_column_text][vc_empty_space height=\u00bb15px\u00bb][\/vc_column_inner][vc_column_inner width=\u00bb1\/3″][vc_column_text css=\u00bb\u00bb]<\/p>\n

Organizador del proyecto<\/h3>\n

[\/vc_column_text][vc_column_text]VDI\/VDE Innovation + Technik GmbH[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_empty_space height=\u00bb60px\u00bb][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbgrid\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb z_index=\u00bb\u00bb][vc_column][vc_empty_space height=\u00bb40″][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbgrid\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb z_index=\u00bb\u00bb css=\u00bb.vc_custom_1720432140000{background-color: #e8e0e0 !important;}\u00bb][vc_column][vc_empty_space height=\u00bb40″][vc_column_text css=\u00bb\u00bb]<\/p>\n

\u00bfInteresado en colaborar en nuestros proyectos de investigaci\u00f3n?<\/h2>\n

[\/vc_column_text][vc_empty_space height=\u00bb15″][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbgrid\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb z_index=\u00bb\u00bb css=\u00bb.vc_custom_1720432148181{background-color: #e8e0e0 !important;}\u00bb][vc_column width=\u00bb1\/6″][\/vc_column][vc_column width=\u00bb2\/3″][vc_column_text css=\u00bb\u00bb]Exploramos el potencial de las tecnolog\u00edas del ma\u00f1ana con proyectos de investigaci\u00f3n e innovaci\u00f3n. Siempre estamos buscando colegas comprometidos que quieran unirse a nosotros en el viaje de XITASO y ayudar a darle forma.[\/vc_column_text][vc_empty_space height=\u00bb15″][vc_column_text css=\u00bb\u00bb]<\/p>\n

Mostrar todas las ofertas<\/a><\/p>\n

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Otros proyectos<\/h2>\n

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Proyecto de investigaci\u00f3n VALISENS<\/div>\n

Fusi\u00f3n de datos de sensores para la conducci\u00f3n aut\u00f3noma<\/h3>\n

[\/vc_column_text][vc_raw_html]JTNDJTJGYSUzRQ==[\/vc_raw_html][\/vc_column_inner][vc_column_inner width=\u00bb1\/3″][vc_raw_html css=\u00bb\u00bb]JTNDYSUyMGhyZWYlM0QlMjIlMkZlcyUyRnByb3llY3RvcyUyRmFkZWxlcyUyRiUyMiUzRQ==[\/vc_raw_html][vc_empty_space height=\u00bb250″ image_repeat=\u00bbno-repeat\u00bb background_image=\u00bb38833″][vc_column_text css=\u00bb\u00bb]<\/p>\n

Proyecto de investigaci\u00f3n ADELeS<\/div>\n

Aprendizaje autom\u00e1tico basado en el conocimiento para la correcci\u00f3n de anomal\u00edas<\/h3>\n

[\/vc_column_text][vc_raw_html]JTNDJTJGYSUzRQ==[\/vc_raw_html][\/vc_column_inner][vc_column_inner width=\u00bb1\/3″][vc_raw_html css=\u00bb\u00bb]JTNDYSUyMGhyZWYlM0QlMjIlMkZlcyUyRnByb3llY3RvcyUyRmtpc3BwLXBsYW5pZmljYWNpb24taW50ZWxpZ2VudGUtZGVsLXBlcnNvbmFsLWRlLWVuZmVybWVyaWElMkYlMjIlM0UlMEE=[\/vc_raw_html][vc_empty_space height=\u00bb250″ image_repeat=\u00bbno-repeat\u00bb background_image=\u00bb38817″][vc_column_text css=\u00bb\u00bb]<\/p>\n

Proyecto de investigaci\u00f3n KISPP<\/div>\n

Planificaci\u00f3n inteligente del personal de enfermer\u00eda<\/h3>\n

[\/vc_column_text][vc_raw_html]JTNDJTJGYSUzRQ==[\/vc_raw_html][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbgrid\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb z_index=\u00bb\u00bb][vc_column][vc_empty_space height=\u00bb30″][vc_column_text css=\u00bb\u00bb]<\/p>\n

Mostrar todos los proyectos<\/a><\/p>\n

[\/vc_column_text][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbgrid\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb z_index=\u00bb\u00bb][vc_column][vc_empty_space height=\u00bb50″ el_class=\u00bbnot-on-mobile\u00bb][vc_empty_space height=\u00bb30″][\/vc_column][\/vc_row][vc_row css_animation=\u00bb\u00bb row_type=\u00bbrow\u00bb use_row_as_full_screen_section=\u00bbno\u00bb type=\u00bbfull_width\u00bb angled_section=\u00bbno\u00bb text_align=\u00bbleft\u00bb background_image_as_pattern=\u00bbwithout_pattern\u00bb z_index=\u00bb\u00bb el_class=\u00bbyour-contact-person\u00bb css=\u00bb.vc_custom_1720088207890{background-color: #e8e0e0 !important;}\u00bb][vc_column][vc_row_inner row_type=\u00bbrow\u00bb type=\u00bbgrid\u00bb text_align=\u00bbleft\u00bb css_animation=\u00bb\u00bb][vc_column_inner][vc_column_text css=\u00bb\u00bb]<\/p>\n

\u00bfEst\u00e1 interesado en un proyecto, un servicio o tiene alguna otra pregunta?<\/h2>\n

[\/vc_column_text][vc_single_image image=\u00bb90048″ img_size=\u00bb120×120″ alignment=\u00bbcenter\u00bb style=\u00bbvc_box_circle_2″ css=\u00bb\u00bb qode_css_animation=\u00bb\u00bb][vc_column_text css=\u00bb\u00bb]<\/p>\n

Dr. Alwin Hoffmann<\/strong><\/p>\n

Tel. +49 821 885 882 231
\nalwin.hoffmann@xitaso.com<\/a><\/p>\n

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