robot-recruit/index.html at main · BenjamFu/robot-recruit · GitHub

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<!DOCTYPE html><html lang="zh-CN"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><style rel="stylesheet" type="text/css">@charset "utf-8";

:root { --bg: #0a0e1a; --card: #111827; --card-hover: #1a2235; --border: #1e293b; --accent: #3b82f6; --accent2: #8b5cf6; --accent3: #06b6d4; --accent4: #f59e0b; --accent5: #ef4444; --accent6: #10b981; --text: #e2e8f0; --text-dim: #94a3b8; --text-bright: #f8fafc; }

* { margin: 0px; padding: 0px; box-sizing: border-box; }

body { background: var(--bg); color: var(--text); font-family: -apple-system, "PingFang SC", "Microsoft YaHei", "Helvetica Neue", sans-serif; line-height: 1.7; }

.container { max-width: 1280px; margin: 0px auto; padding: 0px 24px; }

header { background: linear-gradient(135deg, rgb(15, 23, 42) 0%, rgb(30, 27, 75) 50%, rgb(15, 23, 42) 100%); border-bottom: 1px solid var(--border); padding: 48px 0px 40px; text-align: center; position: relative; overflow: hidden; }

header::before { content: ""; position: absolute; top: -50%; left: -50%; width: 200%; height: 200%; background: radial-gradient(circle at 30% 50%, rgba(59, 130, 246, 0.08) 0%, transparent 50%), radial-gradient(circle at 70% 50%, rgba(139, 92, 246, 0.08) 0%, transparent 50%); }

header h1 { font-size: 2.4rem; font-weight: 800; background: linear-gradient(135deg, rgb(96, 165, 250), rgb(167, 139, 250), rgb(56, 189, 248)) text; -webkit-text-fill-color: transparent; position: relative; }

header p.sub { color: var(--text-dim); font-size: 1.05rem; margin-top: 8px; position: relative; }

.badge-row { display: flex; justify-content: center; gap: 12px; margin-top: 20px; flex-wrap: wrap; position: relative; }

.badge { display: inline-flex; align-items: center; gap: 6px; padding: 6px 16px; border-radius: 20px; font-size: 0.82rem; font-weight: 600; border: 1px solid; }

.badge-blue { color: rgb(96, 165, 250); border-color: rgb(30, 58, 95); background: rgba(59, 130, 246, 0.1); }

.badge-purple { color: rgb(167, 139, 250); border-color: rgb(59, 31, 110); background: rgba(139, 92, 246, 0.1); }

.badge-cyan { color: rgb(34, 211, 238); border-color: rgb(22, 78, 99); background: rgba(6, 182, 212, 0.1); }

nav { background: var(--card); border-bottom: 1px solid var(--border); position: sticky; top: 0px; z-index: 100; }

nav .container { display: flex; gap: 4px; overflow-x: auto; padding: 8px 24px; }

nav a { color: var(--text-dim); text-decoration: none; padding: 8px 16px; border-radius: 8px; font-size: 0.85rem; white-space: nowrap; transition: 0.2s; font-weight: 500; }

nav a:hover, nav a.active { color: var(--text-bright); background: rgba(59, 130, 246, 0.15); }

section { padding: 48px 0px; border-bottom: 1px solid var(--border); }

section:last-child { border-bottom: none; }

.section-header { display: flex; align-items: center; gap: 16px; margin-bottom: 32px; }

.section-num { width: 48px; height: 48px; border-radius: 14px; display: flex; align-items: center; justify-content: center; font-size: 1.3rem; font-weight: 800; color: rgb(255, 255, 255); flex-shrink: 0; }

.section-title h2 { font-size: 1.5rem; font-weight: 700; color: var(--text-bright); }

.section-title p { font-size: 0.9rem; color: var(--text-dim); margin-top: 2px; }

.grid-2 { display: grid; grid-template-columns: 1fr 1fr; gap: 20px; }

.grid-3 { display: grid; grid-template-columns: 1fr 1fr 1fr; gap: 20px; }

@media (max-width: 900px) {
  .grid-2, .grid-3 { grid-template-columns: 1fr; }
}

.card { background: var(--card); border: 1px solid var(--border); border-radius: 14px; padding: 24px; transition: border-color 0.2s; }

.card:hover { border-color: rgba(59, 130, 246, 0.3); }

.card h3 { font-size: 1.05rem; font-weight: 700; color: var(--text-bright); margin-bottom: 12px; display: flex; align-items: center; gap: 8px; }

.card p, .card li { font-size: 0.9rem; color: var(--text); }

.card ul { padding-left: 18px; }

.card ul li { margin-bottom: 4px; }

.card-label { font-size: 0.75rem; font-weight: 600; text-transform: uppercase; letter-spacing: 0.05em; margin-bottom: 8px; }

.flow { background: var(--card); border: 1px solid var(--border); border-radius: 14px; padding: 24px; margin: 20px 0px; overflow-x: auto; }

.flow-steps { display: flex; align-items: center; gap: 0px; flex-wrap: nowrap; min-width: max-content; }

.flow-step { padding: 10px 18px; border-radius: 10px; font-size: 0.82rem; font-weight: 600; white-space: nowrap; text-align: center; }

.flow-arrow { color: var(--text-dim); font-size: 1.2rem; margin: 0px 4px; flex-shrink: 0; }

table { width: 100%; border-collapse: collapse; font-size: 0.88rem; }

th { text-align: left; padding: 10px 14px; background: rgba(59, 130, 246, 0.08); color: var(--accent); font-weight: 600; font-size: 0.8rem; text-transform: uppercase; letter-spacing: 0.04em; border-bottom: 1px solid var(--border); }

td { padding: 10px 14px; border-bottom: 1px solid var(--border); color: var(--text); vertical-align: top; }

tr:hover td { background: rgba(255, 255, 255, 0.02); }

.stars { color: var(--accent4); letter-spacing: 2px; }

.stat-row { display: flex; gap: 16px; flex-wrap: wrap; margin-bottom: 24px; }

.stat-box { flex: 1 1 0%; min-width: 140px; background: var(--card); border: 1px solid var(--border); border-radius: 12px; padding: 16px 20px; text-align: center; }

.stat-box .num { font-size: 1.6rem; font-weight: 800; }

.stat-box .label { font-size: 0.78rem; color: var(--text-dim); margin-top: 4px; }

.conf-card { background: var(--card); border: 1px solid var(--border); border-radius: 14px; padding: 20px 24px; }

.conf-card h4 { font-size: 1rem; font-weight: 700; color: var(--text-bright); margin-bottom: 6px; }

.conf-meta { display: flex; gap: 16px; flex-wrap: wrap; font-size: 0.82rem; color: var(--text-dim); margin-bottom: 10px; }

.conf-meta span { display: inline-flex; align-items: center; gap: 4px; }

.tag { display: inline-block; padding: 2px 10px; border-radius: 6px; font-size: 0.75rem; font-weight: 600; }

.tag-green { background: rgba(16, 185, 129, 0.15); color: rgb(52, 211, 153); }

.tag-yellow { background: rgba(245, 158, 11, 0.15); color: rgb(251, 191, 36); }

.tag-red { background: rgba(239, 68, 68, 0.15); color: rgb(248, 113, 113); }

.tag-blue { background: rgba(59, 130, 246, 0.15); color: rgb(96, 165, 250); }

.accent-1 { color: var(--accent); }

.bg-accent-1 { background: linear-gradient(135deg, rgb(29, 78, 216), rgb(59, 130, 246)); }

.accent-2 { color: var(--accent2); }

.bg-accent-2 { background: linear-gradient(135deg, rgb(109, 40, 217), rgb(139, 92, 246)); }

.accent-3 { color: var(--accent3); }

.bg-accent-3 { background: linear-gradient(135deg, rgb(8, 145, 178), rgb(6, 182, 212)); }

.accent-4 { color: var(--accent4); }

.bg-accent-4 { background: linear-gradient(135deg, rgb(217, 119, 6), rgb(245, 158, 11)); }

.accent-5 { color: var(--accent5); }

.bg-accent-5 { background: linear-gradient(135deg, rgb(220, 38, 38), rgb(239, 68, 68)); }

.accent-6 { color: var(--accent6); }

.bg-accent-6 { background: linear-gradient(135deg, rgb(5, 150, 105), rgb(16, 185, 129)); }

::-webkit-scrollbar { width: 6px; height: 6px; }

::-webkit-scrollbar-track { background: var(--bg); }

::-webkit-scrollbar-thumb { background: rgb(51, 65, 85); border-radius: 3px; }

footer { text-align: center; padding: 40px 0px; color: var(--text-dim); font-size: 0.82rem; border-top: 1px solid var(--border); }</style><style rel="stylesheet" type="text/css">@charset "utf-8";

@keyframes mulepage-svg-glow-dark {
  0%, 100% { color: rgb(255, 255, 255); }
  50% { color: rgb(59, 130, 246); }
}

@keyframes mulepage-svg-glow-light {
  0%, 100% { color: rgb(0, 0, 0); }
  50% { color: rgb(59, 130, 246); }
}

.mulepage-anim-dark { animation: 2.5s ease-in-out 0s infinite normal none running mulepage-svg-glow-dark; }

.mulepage-anim-light { animation: 2.5s ease-in-out 0s infinite normal none running mulepage-svg-glow-light; }

.mulepage-btn-dark { background: rgba(255, 255, 255, 0.03); border: 1px solid rgba(255, 255, 255, 0.08); border-radius: 0px; transition: 0.2s; }

.mulepage-btn-dark:hover { background: rgba(255, 255, 255, 0.08); border-color: rgba(255, 255, 255, 0.15); }

.mulepage-btn-light { background: rgba(0, 0, 0, 0.03); border: 1px solid rgba(0, 0, 0, 0.08); border-radius: 0px; transition: 0.2s; }

.mulepage-btn-light:hover { background: rgba(0, 0, 0, 0.08); border-color: rgba(0, 0, 0, 0.15); }

.mulepage-close-dark { color: rgba(255, 255, 255, 0.3); transition: color 0.2s; }

.mulepage-close-dark:hover { color: rgb(255, 255, 255); }

.mulepage-close-light { color: rgba(0, 0, 0, 0.3); transition: color 0.2s; }

.mulepage-close-light:hover { color: rgb(0, 0, 0); }

#mulepage-footer-link { transition: opacity 0.2s; }

#mulepage-footer-link:hover { opacity: 0.7; }

.mulepage-float { transition: box-shadow 0.2s; will-change: box-shadow; }

.mulepage-float:hover { box-shadow: rgba(0, 0, 0, 0.12) 0px 6px 20px, rgba(0, 0, 0, 0.08) 0px 2px 6px; }

.mulepage-float-close { display: inline-flex; align-items: center; justify-content: center; max-width: 0px; margin-left: 0px; overflow: hidden; opacity: 0; transition: max-width 0.2s, margin-left 0.2s, opacity 0.15s; padding: 0px; border: none; background: none; cursor: pointer; font-size: 16px; line-height: 1; font-weight: 300; height: 16px; will-change: max-width, opacity; }

.mulepage-float:hover .mulepage-float-close { max-width: 14px; margin-left: 4px; opacity: 1; }</style><script>var __mr='all',__md='3237pbkr.mule.page';document.addEventListener('DOMContentLoaded', function () {
  var BAR_HEIGHT = 38;

  // --- detect page theme ---
  var isDark = window.matchMedia && window.matchMedia('(prefers-color-scheme: dark)').matches;

  // fallback: sample body/html background color
  if (!isDark) {
    try {
      var sample = getComputedStyle(document.body).backgroundColor;
      if (sample === 'rgba(0, 0, 0, 0)' || sample === 'transparent') {
        sample = getComputedStyle(document.documentElement).backgroundColor;
      }
      if (sample && sample !== 'rgba(0, 0, 0, 0)' && sample !== 'transparent') {
        var m = sample.match(/\d+/g);
        if (m) {
          var brightness = (parseInt(m[0]) * 299 + parseInt(m[1]) * 587 + parseInt(m[2]) * 114) / 1000;
          isDark = brightness < 128;
        }
      }
    } catch (e) {}
  }

  // --- shared CSS (always injected into <head>) ---
  var SHARED_CSS = '<style>' +
    '@keyframes mulepage-svg-glow-dark{0%,100%{color:#ffffff}50%{color:#3b82f6}}' +
    '@keyframes mulepage-svg-glow-light{0%,100%{color:#000000}50%{color:#3b82f6}}' +
    '.mulepage-anim-dark{animation:mulepage-svg-glow-dark 2.5s ease-in-out infinite}' +
    '.mulepage-anim-light{animation:mulepage-svg-glow-light 2.5s ease-in-out infinite}' +
    '.mulepage-btn-dark{background:rgba(255,255,255,0.03);border:1px solid rgba(255,255,255,0.08);border-radius:0;transition:all 0.2s ease}' +
    '.mulepage-btn-dark:hover{background:rgba(255,255,255,0.08);border-color:rgba(255,255,255,0.15)}' +
    '.mulepage-btn-light{background:rgba(0,0,0,0.03);border:1px solid rgba(0,0,0,0.08);border-radius:0;transition:all 0.2s ease}' +
    '.mulepage-btn-light:hover{background:rgba(0,0,0,0.08);border-color:rgba(0,0,0,0.15)}' +
    '.mulepage-close-dark{color:rgba(255,255,255,0.3);transition:color 0.2s ease}' +
    '.mulepage-close-dark:hover{color:#ffffff}' +
    '.mulepage-close-light{color:rgba(0,0,0,0.3);transition:color 0.2s ease}' +
    '.mulepage-close-light:hover{color:#000000}' +
    '#mulepage-footer-link{transition:opacity 0.2s ease}' +
    '#mulepage-footer-link:hover{opacity:0.7}' +
    '.mulepage-float{transition:box-shadow 0.2s ease;will-change:box-shadow}' +
    '.mulepage-float:hover{box-shadow:0 6px 20px rgba(0,0,0,0.12),0 2px 6px rgba(0,0,0,0.08)}' +
    '.mulepage-float-close{display:inline-flex;align-items:center;justify-content:center;max-width:0;margin-left:0;overflow:hidden;opacity:0;transition:max-width 0.2s ease,margin-left 0.2s ease,opacity 0.15s ease;padding:0;border:none;background:none;cursor:pointer;font-size:16px;line-height:1;font-weight:300;height:16px;will-change:max-width,opacity}' +
    '.mulepage-float:hover .mulepage-float-close{max-width:14px;margin-left:4px;opacity:1}' +
    '</style>';

  // always inject shared CSS into <head> so it survives banner removal
  document.head.insertAdjacentHTML('beforeend', SHARED_CSS);

  // --- SVG icon (shared, rx=0 for sharp corners) ---
  var ICON16 = '<svg width="16" height="16" viewBox="0 0 36 36" fill="none" xmlns="http://www.w3.org/2000/svg">' +
    '<rect width="36" height="36" rx="0" fill="#FBF9F6"/><g clip-path="url(#c_top)">' +
    '<path d="M6.387 21.732v8.895H18.762V28.5h2.32v1.16h8.121V28.5h1.16v-7.928h-1.16v-1.16h-4.64v-1.16h-1.16v-1.16h-1.16v-1.16h-1.16v-1.16h-1.16v-1.16h3.287v-1.934h3.48V9.357H16.442v3.48h-2.128V6.07h-2.32v2.127H9.674v3.48H7.547v10.055H6.387Z" fill="#000"/>' +
    '<path d="M13.154 21.732v-4.447h1.16v-1.16h4.448v4.447h-1.16v1.16h-4.448Z" fill="#fff"/>' +
    '<rect x="15.281" y="18.252" width="2.32" height="2.32" fill="#000"/>' +
    '<path d="M21.082 27.34v-5.608h1.16v-1.16h5.801v1.16h1.16v5.608h-1.16V28.5h-5.801v-1.16h-1.16Z" fill="#fff"/>' +
    '<path d="M26.883 21.732h-2.32v1.16h1.16v1.16h1.16v-2.32Z" fill="#000"/>' +
    '<path d="M22.242 24.053v2.32h1.16v1.16h3.48v-1.16h-2.32v-1.16h-1.16v-1.16h-1.16Z" fill="#000"/>' +
    '</g><defs><clipPath id="c_top"><rect width="24.75" height="24.75" fill="#fff" transform="translate(6 6)"/></clipPath></defs></svg>';

  var ICON16_FOOT = ICON16.replace(/c_top/g, 'c_foot');

  // --- SVG brand text ---
  var BRAND_SVG_DARK = '<svg class="mulepage-anim-dark" width="58" height="16" viewBox="0 0 58 16" fill="none" xmlns="http://www.w3.org/2000/svg" style="user-select:none;">' +
    '<text x="0" y="13" font-family="inherit" font-weight="600" font-size="13" fill="currentColor">MuleRun</text></svg>';

  var BRAND_SVG_LIGHT = '<svg id="mulepage-footer-svg-text" class="mulepage-anim-light" width="56" height="15" viewBox="0 0 58 16" fill="none" xmlns="http://www.w3.org/2000/svg" style="user-select:none;">' +
    '<text x="0" y="13" font-family="inherit" font-weight="600" font-size="13" fill="currentColor">MuleRun</text></svg>';

  // --- banner (adapts to page theme) ---
  var bannerBg = isDark ? '#050505' : '#ffffff';
  var bannerBorder = isDark ? 'rgba(255,255,255,0.08)' : 'rgba(0,0,0,0.06)';
  var bannerColor = isDark ? '#fff' : '#000';
  var bannerSubColor = isDark ? 'rgba(255,255,255,0.45)' : 'rgba(0,0,0,0.45)';
  var bannerTextColor = isDark ? 'rgba(255,255,255,0.65)' : 'rgba(0,0,0,0.65)';
  var bannerArrowColor = isDark ? 'rgba(255,255,255,0.4)' : 'rgba(0,0,0,0.4)';
  var bannerSepColor = isDark ? 'rgba(255,255,255,0.15)' : 'rgba(0,0,0,0.15)';
  var bannerBtnClass = isDark ? 'mulepage-btn-dark' : 'mulepage-btn-light';
  var bannerCloseClass = isDark ? 'mulepage-close-dark' : 'mulepage-close-light';
  var bannerBrandSvg = isDark ? BRAND_SVG_DARK : BRAND_SVG_LIGHT.replace('mulepage-footer-svg-text', 'mulepage-bar-svg-text');

  var BANNER = '<div id="mulepage-bar" style="position:fixed;top:0;left:0;width:100%;height:' + BAR_HEIGHT + 'px;' +
    'background:' + bannerBg + ';border-bottom:1px solid ' + bannerBorder + ';color:' + bannerColor + ';' +
    'display:flex;align-items:center;justify-content:center;gap:10px;' +
    'font-family:Inter,-apple-system,BlinkMacSystemFont,\'Segoe UI\',\'Helvetica Neue\',sans-serif;' +
    'font-size:13px;z-index:2147483647;letter-spacing:0.02em;">' +
    '<span style="color:' + bannerSubColor + ';font-size:12px;text-transform:uppercase;letter-spacing:0.05em;">Built with</span>' +
    '<span id="mulepage-bar-link" class="' + bannerBtnClass + '" style="display:inline-flex;align-items:center;gap:6px;' +
    'padding:3px 10px 3px 6px;cursor:pointer;">' +
    ICON16 + bannerBrandSvg + '</span>' +
    '<span style="color:' + bannerSepColor + ';margin:0 2px;">|</span>' +
    '<span style="color:' + bannerTextColor + ';">Create your own website in minutes</span>' +
    '<span style="color:' + bannerArrowColor + ';margin-left:-2px;">\u2192</span>' +
    '<button id="mulepage-bar-close" class="' + bannerCloseClass + '" style="position:absolute;right:16px;background:none;border:none;border-radius:0;' +
    'font-size:18px;cursor:pointer;line-height:1;padding:4px;font-weight:300;">\u00d7</button>' +
    '</div>';

  // --- floating widget (bottom-right, glassmorphism) ---
  var floatBg = isDark ? 'rgba(30,30,30,0.65)' : 'rgba(255,255,255,0.65)';
  var floatBorder = isDark ? 'rgba(255,255,255,0.12)' : 'rgba(0,0,0,0.08)';
  var floatShadow = isDark
    ? '0 4px 16px rgba(0,0,0,0.4),0 1px 4px rgba(0,0,0,0.3)'
    : '0 4px 16px rgba(0,0,0,0.08),0 1px 4px rgba(0,0,0,0.06)';
  var floatBrandSvg = isDark ? BRAND_SVG_LIGHT.replace('mulepage-anim-light', 'mulepage-anim-dark') : BRAND_SVG_LIGHT;
  var floatCloseColor = isDark ? 'rgba(255,255,255,0.35)' : 'rgba(0,0,0,0.3)';
  var floatCloseHover = isDark ? '#ffffff' : '#000000';
  var byColor = isDark ? 'rgba(255,255,255,0.6)' : 'rgba(0,0,0,0.6)';

  var FOOTER = '<div id="mulepage-footer" class="mulepage-float" style="position:fixed !important;bottom:16px !important;right:16px !important;z-index:2147483646;' +
    'display:inline-flex;align-items:center;padding:6px 12px 6px 6px;cursor:pointer;' +
    'background:' + floatBg + ';border:1px solid ' + floatBorder + ';border-radius:4px;' +
    'backdrop-filter:blur(12px);-webkit-backdrop-filter:blur(12px);' +
    'box-shadow:' + floatShadow + ';' +
    'font-family:Inter,-apple-system,BlinkMacSystemFont,\'Segoe UI\',\'Helvetica Neue\',sans-serif;">' +
    '<span id="mulepage-footer-link" style="display:inline-flex;align-items:center;">' +
    ICON16_FOOT +
    '<span style="font-size:11px;font-weight:400;margin:0 4px 0 6px;color:' + byColor + ';">by</span>' +
    floatBrandSvg +
    '</span>' +
    '</div>';

  // --- insert banner (only when mode is "all") ---
  if (__mr === 'all') {
    document.body.insertAdjacentHTML('afterbegin', BANNER);

    // brand link click
    document.getElementById('mulepage-bar-link').addEventListener('click', function () {
      window.open('https://mulerun.com?utm_source=pages&utm_medium=banner&utm_campaign=pages_branding&utm_content=top_bar', '_blank', 'noopener,noreferrer');
    });

    // replace favicon
    var oldIcons = document.querySelectorAll('link[rel="icon"],link[rel="shortcut icon"]');
    for (var k = 0; k < oldIcons.length; k++) oldIcons[k].remove();
    var fi = document.createElement('link');
    fi.rel = 'icon'; fi.type = 'image/svg+xml'; fi.href = 'https://mule.page/favicon.svg';
    document.head.appendChild(fi);

    // push down normal-flow content (accumulate on existing padding-top)
    var origPT = parseFloat(getComputedStyle(document.body).paddingTop) || 0;
    document.body.style.paddingTop = (origPT + BAR_HEIGHT) + 'px';

    // push down all existing position:fixed elements
    var all = document.querySelectorAll('*');
    var shifted = [];
    for (var i = 0; i < all.length; i++) {
      var el = all[i];
      if (el.id && el.id.indexOf('mulepage') === 0) continue;
      var cs = getComputedStyle(el);
      if (cs.position === 'fixed') {
        var t = parseFloat(cs.top);
        if (isNaN(t)) t = 0;
        el.style.top = (t + BAR_HEIGHT) + 'px';
        shifted.push({ el: el, orig: t });
      }
    }

    // close handler: restore everything
    document.getElementById('mulepage-bar-close').addEventListener('click', function () {
      document.getElementById('mulepage-bar').remove();
      document.body.style.paddingTop = origPT + 'px';
      for (var j = 0; j < shifted.length; j++) {
        shifted[j].el.style.top = shifted[j].orig + 'px';
      }
    });
  }

  // --- insert floating widget (only when __mr is set) ---
  if (__mr) {
    document.body.insertAdjacentHTML('beforeend', FOOTER);

    // footer link click → open mulerun.com
    var footerLink = document.getElementById('mulepage-footer-link');
    if (footerLink) {
      footerLink.addEventListener('click', function () {
        window.open('https://mulerun.com/chat?utm_source=pages&utm_medium=banner&utm_campaign=pages_branding&utm_content=bottom_bar', '_blank', 'noopener,noreferrer');
      });
    }

    // paid users (footer-only mode): add close button on hover
    if (__mr === 'footer') {
      var floatEl = document.getElementById('mulepage-footer');
      if (floatEl) {
        var closeBtn = document.createElement('button');
        closeBtn.className = 'mulepage-float-close';
        closeBtn.style.color = floatCloseColor;
        closeBtn.textContent = '\u00d7';
        closeBtn.addEventListener('mouseenter', function () { closeBtn.style.color = floatCloseHover; });
        closeBtn.addEventListener('mouseleave', function () { closeBtn.style.color = floatCloseColor; });
        closeBtn.addEventListener('click', function (e) {
          e.stopPropagation();
          floatEl.remove();
        });
        floatEl.appendChild(closeBtn);
      }
    }
  }

  // --- inject canonical link (all users) ---
  var canon = document.createElement('link');
  canon.rel = 'canonical';
  canon.href = 'https://' + location.hostname + '/';
  document.head.appendChild(canon);

  // --- inject og meta tags (all users) ---
  var ogDomain = __md;
  var ogTitle = document.title || ogDomain;
  var ogTags = [
    ['og:title', ogTitle],
    ['og:url', 'https://' + location.hostname + '/'],
    ['og:type', 'website'],
    ['og:image', 'https://mule.page/og/' + ogDomain + '.webp']
  ];
  for (var n = 0; n < ogTags.length; n++) {
    var existing = document.querySelector('meta[property="' + ogTags[n][0] + '"]');
    if (existing) existing.remove();
    var meta = document.createElement('meta');
    meta.setAttribute('property', ogTags[n][0]);
    meta.setAttribute('content', ogTags[n][1]);
    document.head.appendChild(meta);
  }
});
</script>

<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>具身智能人才地图 — 高招专家工作手册</title>

<link rel="icon" type="image/svg+xml" href="https://mule.page/favicon.svg"><link rel="canonical" href="https://3237pbkr.mule.page/"><meta property="og:title" content="具身智能人才地图 — 高招专家工作手册"><meta property="og:url" content="https://3237pbkr.mule.page/"><meta property="og:type" content="website"><meta property="og:image" content="https://mule.page/og/3237pbkr.mule.page.webp"></head>
<body style="padding-top: 38px;">
<!-- BENJAMIN EXPERT BANNER -->
<div id="benjamin-banner" style="
  background: linear-gradient(135deg, #0a0e1a 0%, #1a1a3e 50%, #0f2460 100%);
  color: #e2e8f0;
  padding: 40px 20px;
  text-align: center;
  position: relative;
  z-index: 50;
  border-bottom: 2px solid rgba(59,130,246,0.3);
">
  <div style="max-width: 800px; margin: 0 auto; display: flex; align-items: center; justify-content: center; gap: 40px; flex-wrap: wrap;">
    <div style="flex-shrink: 0;">
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    <h1>具身智能 · 人才地图</h1>
    <p class="sub">高招专家工作手册 — 六大稀缺岗位深度解析</p>
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      <span class="badge badge-blue">全球人才池 &lt; 1,000人</span>
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<!-- OVERVIEW SECTION -->
<section id="overview">
  <div class="section-header">
    <div class="section-title">
      <h2>六大稀缺岗位总览</h2>
      <p>具身智能机器人核心技术岗位 · 全球人才竞争格局</p>
    </div>
  </div>

  <div class="stat-row">
    <div class="stat-box"><div class="num accent-1">200-300</div><div class="label">基础模型研究员<br>全球人才池</div></div>
    <div class="stat-box"><div class="num accent-2">100-150</div><div class="label">步态控制专家<br>全球人才池</div></div>
    <div class="stat-box"><div class="num accent-3">80-120</div><div class="label">灵巧操作研究员<br>全球人才池</div></div>
    <div class="stat-box"><div class="num accent-4">150-250</div><div class="label">仿真迁移专家<br>全球人才池</div></div>
    <div class="stat-box"><div class="num accent-5">2,000-3,000</div><div class="label">高级SLAM工程师<br>全球人才池</div></div>
    <div class="stat-box"><div class="num accent-6">100-200</div><div class="label">灵巧手工程师<br>全球人才池</div></div>
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  <div class="card" style="overflow-x:auto;">
    <table>
      <thead>
        <tr>
          <th>岗位</th>
          <th>全球人才池</th>
          <th>稀缺度</th>
          <th>核心人才来源</th>
          <th>寻访难度</th>
          <th>薪酬参考（国内）</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <td><strong class="accent-1">基础模型研究员</strong><br><small>VLA / 扩散策略</small></td>
          <td>约200-300人</td>
          <td><span class="stars">★★★★☆</span></td>
          <td>斯坦福 / 伯克利 / 卡内基梅隆</td>
          <td><span class="tag tag-red">高（极度抢手）</span></td>
          <td>150-500万+</td>
        </tr>
        <tr>
          <td><strong class="accent-2">步态控制专家</strong><br><small>强化学习 Locomotion</small></td>
          <td>约100-150人</td>
          <td><span class="stars">★★★★★</span></td>
          <td>苏黎世联邦理工 RSL 为核心</td>
          <td><span class="tag tag-red">极高</span></td>
          <td>100-300万</td>
        </tr>
        <tr>
          <td><strong class="accent-3">灵巧操作研究员</strong><br><small>灵巧操作学习</small></td>
          <td>约80-120人</td>
          <td><span class="stars">★★★★★</span></td>
          <td>伯克利 / 普林斯顿 / 麻省理工 / 北大</td>
          <td><span class="tag tag-red">极高</span></td>
          <td>120-400万</td>
        </tr>
        <tr>
          <td><strong class="accent-4">仿真迁移专家</strong><br><small>Sim-to-Real</small></td>
          <td>约150-250人</td>
          <td><span class="stars">★★★★☆</span></td>
          <td>伯克利 / 英伟达 / 苏黎世联邦理工</td>
          <td><span class="tag tag-yellow">高</span></td>
          <td>80-300万</td>
        </tr>
        <tr>
          <td><strong class="accent-5">高级SLAM工程师</strong><br><small>定位与建图</small></td>
          <td>约2,000-3,000人</td>
          <td><span class="stars">★★★☆☆</span></td>
          <td>大疆 / 自动驾驶 / 港科大 / 苏黎世联邦理工</td>
          <td><span class="tag tag-yellow">中高（需筛选适配性）</span></td>
          <td>60-200万</td>
        </tr>
        <tr>
          <td><strong class="accent-6">灵巧手工程师</strong><br><small>机械设计</small></td>
          <td>约100-200人</td>
          <td><span class="stars">★★★★★</span></td>
          <td>Shadow Robot / 卡内基梅隆 / 斯坦福 / 哈工大</td>
          <td><span class="tag tag-red">极高（最稀缺）</span></td>
          <td>50-150万</td>
        </tr>
      </tbody>
    </table>
  </div>
</section>

<!-- ROLE 1 -->
<section id="role1">
  <div class="section-header">
    <div class="section-num bg-accent-1">1</div>
    <div class="section-title">
      <h2>基础模型研究员（VLA / 扩散策略）</h2>
      <p>机器人的"大脑决策层" · 全球约200-300人 · 稀缺度 ★★★★☆</p>
    </div>
  </div>

  <div class="grid-2">
    <div class="card">
      <h3><span class="accent-1">◆</span> 工作内容</h3>
      <ul>
        <li>设计和训练"视觉-语言-动作"（VLA）大模型架构（RT-2、Octo、π0等路线）</li>
        <li>基于扩散策略生成多模态动作轨迹</li>
        <li>构建大规模机器人操作数据集（遥操作采集 + 仿真数据）</li>
        <li>模型在真实机器人上的部署、微调与迭代</li>
      </ul>
    </div>
    <div class="card">
      <h3><span class="accent-1">◆</span> 稀缺性原因</h3>
      <ul>
        <li>方向从2023年RT-2发布才成型，存在不到3年</li>
        <li>需同时精通大语言模型 + 计算机视觉 + 机器人控制三个领域</li>
        <li>训练依赖大量真实机器人数据，全球仅少数实验室有条件</li>
        <li>博士培养周期4-6年，人才管线严重滞后于需求</li>
      </ul>
    </div>
  </div>

  <div class="flow">
    <p class="card-label accent-1">作用链路</p>
    <div class="flow-steps">
      <div class="flow-step" style="background:rgba(59,130,246,0.15);color:#60a5fa;">人类语言指令</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(59,130,246,0.2);color:#93bbfc;">VLA模型接收语言+图像</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(59,130,246,0.25);color:#93bbfc;">模型推理生成动作序列</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(59,130,246,0.3);color:#bdd4fc;">下发运动控制器</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(59,130,246,0.4);color:#fff;">关节执行完成任务</div>
    </div>
  </div>

  <div class="grid-2">
    <div class="card">
      <h3><span class="accent-1">◆</span> 目标公司</h3>
      <table>
        <thead><tr><th>海外</th><th>国内</th></tr></thead>
        <tbody>
          <tr><td>Physical Intelligence</td><td>智元机器人</td></tr>
          <tr><td>谷歌 DeepMind</td><td>银河通用</td></tr>
          <tr><td>Figure AI</td><td>星动纪元</td></tr>
          <tr><td>特斯拉 Optimus</td><td>国内头部人形机器人企业</td></tr>
          <tr><td>英伟达（GR00T）</td><td>宇树科技</td></tr>
          <tr><td>Meta FAIR</td><td>小鹏鹏行</td></tr>
          <tr><td>丰田研究院</td><td>华为</td></tr>
        </tbody>
      </table>
    </div>
    <div class="card">
      <h3><span class="accent-1">◆</span> 学校与关键教授</h3>
      <table>
        <thead><tr><th>学校/实验室</th><th>关键人物</th></tr></thead>
        <tbody>
          <tr><td>斯坦福 SAIL/IRIS</td><td>Chelsea Finn — 扩散策略领军</td></tr>
          <tr><td>伯克利 BAIR</td><td>Sergey Levine — 机器人学习开山级</td></tr>
          <tr><td>哥伦比亚/普林斯顿</td><td>Shuran Song — π0核心贡献</td></tr>
          <tr><td>卡内基梅隆机器人所</td><td>Deepak Pathak — 通用基础模型</td></tr>
          <tr><td>清华交叉信息院</td><td>国内VLA最早布局</td></tr>
          <tr><td>北京大学</td><td>王鹤 — 灵巧操作+基础模型</td></tr>
          <tr><td>上海交通大学</td><td>卢策吾 — 具身智能+视觉动作</td></tr>
        </tbody>
      </table>
    </div>
  </div>

  <div class="card" style="margin-top:20px;">
    <h3><span class="accent-1">◆</span> 寻访方式与薪酬</h3>
    <div class="grid-2" style="gap:16px;">
      <div>
        <p class="card-label accent-1">寻访渠道</p>
        <ul>
          <li><strong>论文反查</strong>：谷歌学术搜索"VLA""Diffusion Policy""RT-2"，锁定作者</li>
          <li><strong>会议重点</strong>：CoRL（最精准）、NeurIPS、ICRA</li>
          <li><strong>开源追踪</strong>：Octo、LeRobot（HuggingFace）核心贡献者</li>
          <li><strong>领英关键词</strong>："foundation model" AND "robotics"</li>
        </ul>
      </div>
      <div>
        <p class="card-label accent-1">薪酬参考</p>
        <ul>
          <li>美国：年薪总包约 220-500万人民币</li>
          <li>国内：约 150-500万（顶尖可达千万级）</li>
        </ul>
      </div>
    </div>
  </div>
</section>

<!-- ROLE 2 -->
<section id="role2">
  <div class="section-header">
    <div class="section-num bg-accent-2">2</div>
    <div class="section-title">
      <h2>强化学习步态控制专家</h2>
      <p>机器人的"小脑" · 全球约100-150人 · 稀缺度 ★★★★★</p>
    </div>
  </div>

  <div class="grid-2">
    <div class="card">
      <h3><span class="accent-2">◆</span> 工作内容</h3>
      <ul>
        <li>在仿真器（英伟达 Isaac Gym / MuJoCo）中设计奖励函数和训练环境</li>
        <li>训练步态策略网络——行走、跑步、跳跃、上下楼梯</li>
        <li>仿真到真实迁移，真实硬件上调试验证</li>
        <li>摔倒恢复、外力抵抗、动态平衡等极端场景处理</li>
      </ul>
    </div>
    <div class="card">
      <h3><span class="accent-2">◆</span> 稀缺性原因</h3>
      <ul>
        <li>人形双足远比四足难——支撑面小、重心高、动力学天然不稳定</li>
        <li>需同时具备刚体动力学 + 强化学习算法 + 真机调试三方面能力</li>
        <li>过去十年大部分RL研究停留在仿真游戏，做过实体机器人的人极少</li>
        <li>全球拥有人形机器人硬件平台的实验室不超过20个</li>
      </ul>
    </div>
  </div>

  <div class="flow">
    <p class="card-label accent-2">作用链路</p>
    <div class="flow-steps">
      <div class="flow-step" style="background:rgba(139,92,246,0.15);color:#a78bfa;">上层任务指令"走到A点"</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(139,92,246,0.2);color:#c4b5fd;">路径规划器生成路径</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(139,92,246,0.25);color:#c4b5fd;">步态策略接收本体状态</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(139,92,246,0.3);color:#ddd6fe;">输出关节目标力矩</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(139,92,246,0.4);color:#fff;">机器人稳定行走</div>
    </div>
  </div>

  <div class="grid-2">
    <div class="card">
      <h3><span class="accent-2">◆</span> 目标公司</h3>
      <table>
        <thead><tr><th>海外</th><th>国内</th></tr></thead>
        <tbody>
          <tr><td>Agility Robotics（亚马逊仓库部署）</td><td>宇树科技</td></tr>
          <tr><td>波士顿动力（Atlas）</td><td>林希动力学</td></tr>
          <tr><td>特斯拉 Optimus</td><td>星动纪元</td></tr>
          <tr><td>Figure AI</td><td>智元机器人</td></tr>
          <tr><td>1X Technologies（挪威）</td><td>小鹏鹏行</td></tr>
          <tr><td>Swiss-Mile（苏黎世联邦理工孵化）</td><td>傅利叶智能</td></tr>
          <tr><td>Apptronik</td><td>国内头部人形机器人企业</td></tr>
        </tbody>
      </table>
    </div>
    <div class="card">
      <h3><span class="accent-2">◆</span> 学校与关键教授</h3>
      <table>
        <thead><tr><th>学校/实验室</th><th>关键人物</th></tr></thead>
        <tbody>
          <tr><td><strong>苏黎世联邦理工 RSL</strong></td><td><strong>Marco Hutter — 全球最重要来源</strong></td></tr>
          <tr><td>伯克利</td><td>Pieter Abbeel、Sergey Levine</td></tr>
          <tr><td>卡内基梅隆</td><td>Jessica Hodgins、Deepak Pathak</td></tr>
          <tr><td>麻省理工仿生实验室</td><td>Sangbae Kim — Cheetah团队</td></tr>
          <tr><td>韩国科学技术院</td><td>HUBO人形机器人长期积累</td></tr>
          <tr><td>清华 / 浙大</td><td>交叉信息院 / 四足机器人实验室</td></tr>
        </tbody>
      </table>
    </div>
  </div>

  <div class="card" style="margin-top:20px;">
    <h3><span class="accent-2">◆</span> 寻访方式与薪酬</h3>
    <div class="grid-2" style="gap:16px;">
      <div>
        <p class="card-label accent-2">寻访渠道</p>
        <ul>
          <li><strong>第一优先级</strong>：追踪苏黎世联邦理工RSL组历届博士/博后去向</li>
          <li>Agility Robotics和波士顿动力离职员工</li>
          <li><strong>会议</strong>：ICRA、IROS（步态控制专题）、CoRL</li>
          <li><strong>领英</strong>："locomotion" AND "reinforcement learning" AND "humanoid"</li>
        </ul>
      </div>
      <div>
        <p class="card-label accent-2">薪酬参考</p>
        <ul>
          <li>美国：年薪总包约 180-400万人民币</li>
          <li>国内：约 100-300万</li>
        </ul>
      </div>
    </div>
  </div>
</section>

<!-- ROLE 3 -->
<section id="role3">
  <div class="section-header">
    <div class="section-num bg-accent-3">3</div>
    <div class="section-title">
      <h2>灵巧操作学习研究员</h2>
      <p>机器人的"手部大脑" · 全球约80-120人 · 稀缺度 ★★★★★</p>
    </div>
  </div>

  <div class="grid-2">
    <div class="card">
      <h3><span class="accent-3">◆</span> 工作内容</h3>
      <ul>
        <li>设计灵巧操作学习算法（模仿学习、强化学习、扩散策略）</li>
        <li>触觉传感器数据融合与接触状态估计</li>
        <li>多指协调控制策略（20+自由度协调运动）</li>
        <li>从人类遥操作演示数据中学习精细操作技能</li>
      </ul>
    </div>
    <div class="card">
      <h3><span class="accent-3">◆</span> 稀缺性原因</h3>
      <ul>
        <li>灵巧手硬件极贵（单只手35万-140万人民币），大部分实验室无力购买</li>
        <li>接触密集型操作的仿真到真实迁移差距极大</li>
        <li>2020-2021年OpenAI解散整个机器人团队，最大人才来源一度断裂</li>
        <li>需同时精通机器学习 + 触觉感知 + 手部运动学，交叉门槛极高</li>
      </ul>
    </div>
  </div>

  <div class="flow">
    <p class="card-label accent-3">作用链路</p>
    <div class="flow-steps">
      <div class="flow-step" style="background:rgba(6,182,212,0.15);color:#22d3ee;">大脑层发出操作意图</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(6,182,212,0.2);color:#67e8f9;">策略接收视觉+触觉</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(6,182,212,0.25);color:#67e8f9;">生成多指关节序列</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(6,182,212,0.3);color:#a5f3fc;">灵巧手执行精细操作</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(6,182,212,0.4);color:#fff;">触觉反馈实时调整</div>
    </div>
  </div>

  <div class="grid-2">
    <div class="card">
      <h3><span class="accent-3">◆</span> 目标公司</h3>
      <table>
        <thead><tr><th>海外</th><th>国内</th></tr></thead>
        <tbody>
          <tr><td>特斯拉 Optimus（22自由度手）</td><td>智元机器人</td></tr>
          <tr><td>Physical Intelligence</td><td>因时机器人（2025年出货1万只手）</td></tr>
          <tr><td>亚马逊机器人</td><td>国内头部人形机器人企业</td></tr>
          <tr><td>Figure AI</td><td>银河通用</td></tr>
          <tr><td>丰田研究院</td><td>星动纪元</td></tr>
          <tr><td>英伟达 / Shadow Robot</td><td>腾讯机器人实验室 / 小米</td></tr>
        </tbody>
      </table>
    </div>
    <div class="card">
      <h3><span class="accent-3">◆</span> 学校与关键教授</h3>
      <table>
        <thead><tr><th>学校/实验室</th><th>关键人物</th></tr></thead>
        <tbody>
          <tr><td>伯克利 AUTOLAB</td><td>Ken Goldberg — 抓取学习奠基人</td></tr>
          <tr><td>普林斯顿</td><td>Shuran Song — 视触觉融合</td></tr>
          <tr><td>麻省理工</td><td>Russ Tedrake — 接触动力学</td></tr>
          <tr><td>斯坦福</td><td>Jeannette Bohg — 人类演示学习</td></tr>
          <tr><td>哥伦比亚</td><td>Matei Ciocarlie — 欠驱动抓取</td></tr>
          <tr><td><strong>北京大学</strong></td><td><strong>王鹤 — 国内最强组之一</strong></td></tr>
        </tbody>
      </table>
    </div>
  </div>

  <div class="card" style="margin-top:20px;">
    <h3><span class="accent-3">◆</span> 寻访方式与薪酬</h3>
    <div class="grid-2" style="gap:16px;">
      <div>
        <p class="card-label accent-3">寻访渠道</p>
        <ul>
          <li><strong>追踪前OpenAI机器人团队成员去向</strong>（散落在PI、Covariant、Figure AI等）</li>
          <li>北大王鹤组、普林斯顿Song组博士生是最直接候选人来源</li>
          <li><strong>会议</strong>：CoRL（最精准）、RSS、ICRA</li>
          <li><strong>领英</strong>："dexterous manipulation" AND "learning"</li>
        </ul>
      </div>
      <div>
        <p class="card-label accent-3">薪酬参考</p>
        <ul>
          <li>美国：年薪总包约 200-470万人民币</li>
          <li>国内：约 120-400万</li>
        </ul>
      </div>
    </div>
  </div>
</section>

<!-- ROLE 4 -->
<section id="role4">
  <div class="section-header">
    <div class="section-num bg-accent-4">4</div>
    <div class="section-title">
      <h2>仿真到真实迁移专家</h2>
      <p>仿真训练与真实部署的桥梁 · 全球约150-250人 · 稀缺度 ★★★★☆</p>
    </div>
  </div>

  <div class="grid-2">
    <div class="card">
      <h3><span class="accent-4">◆</span> 工作内容</h3>
      <ul>
        <li>构建高保真仿真环境（英伟达 Isaac Sim、MuJoCo等物理引擎）</li>
        <li>设计域随机化参数方案——让策略对环境差异具备鲁棒性</li>
        <li>系统辨识——精确测量真实机器人物理参数并反馈到仿真</li>
        <li>搭建大规模并行仿真训练基础设施（数十亿步训练）</li>
        <li>分析仿真与真实之间的差距并系统性弥合</li>
      </ul>
    </div>
    <div class="card">
      <h3><span class="accent-4">◆</span> 稀缺性原因</h3>
      <ul>
        <li>需同时精通物理仿真引擎开发 + 强化学习算法 + 真实硬件调试</li>
        <li>全球每年相关博士毕业约100人，但中国人形机器人招聘需求暴增超400%</li>
        <li>英伟达 Isaac 生态刚起步，深度使用者有限</li>
        <li>发过仿真论文的人很多，完成过真机闭环迁移的人远少于此</li>
      </ul>
    </div>
  </div>

  <div class="flow">
    <p class="card-label accent-4">作用链路</p>
    <div class="flow-steps">
      <div class="flow-step" style="background:rgba(245,158,11,0.15);color:#fbbf24;">真机参数测量</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(245,158,11,0.2);color:#fcd34d;">搭建仿真环境</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(245,158,11,0.25);color:#fcd34d;">大规模并行训练策略</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(245,158,11,0.3);color:#fde68a;">域随机化增强鲁棒性</div>
      <span class="flow-arrow">→</span>
      <div class="flow-step" style="background:rgba(245,158,11,0.4);color:#fff;">部署真机并迭代</div>
    </div>
  </div>

  <div class="grid-2">
    <div class="card">
      <h3><span class="accent-4">◆</span> 目标公司</h3>
      <table>
        <thead><tr><th>海外</th><th>国内</th></tr></thead>
        <tbody>
          <tr><td>英伟达（Isaac Sim/Lab/Gym团队）</td><td>智元机器人</td></tr>
          <tr><td>谷歌 DeepMind</td><td>宇树科技</td></tr>
          <tr><td>Physical Intelligence</td><td>国内头部人形机器人企业</td></tr>
          <tr><td>特斯拉</td><td>银河通用</td></tr>
          <tr><td>Figure AI</td><td>星动纪元</td></tr>
          <tr><td>Agility Robotics / 波士顿动力</td><td>小鹏鹏行 / 傅利叶智能</td></tr>
        </tbody>
      </table>
    </div>
    <div class="card">
      <h3><span class="accent-4">◆</span> 学校与关键教授</h3>
      <table>
        <thead><tr><th>学校/实验室</th><th>关键人物</th></tr></thead>
        <tbody>
          <tr><td>伯克利</td><td>Pieter Abbeel、Sergey Levine — 域随机化先驱</td></tr>
          <tr><td>斯坦福</td><td>Chelsea Finn — 元学习迁移</td></tr>
          <tr><td>卡内基梅隆</td><td>Deepak Pathak — 视觉运动策略迁移</td></tr>
          <tr><td>加州大学圣地亚哥</td><td>Xiaolong Wang — 操作迁移</td></tr>
          <tr><td>苏黎世联邦理工</td><td>Marco Hutter — 工程化落地</td></tr>
          <tr><td>清华 / 北大</td><td>交叉信息院 / 智能科学系</td></tr>
        </tbody>
      </table>
    </div>
  </div>

  <div class="card" style="margin-top:20px;">
    <h3><span class="accent-4">◆</span> 寻访方式与薪酬</h3>
    <div class="grid-2" style="gap:16px;">
      <div>
        <p class="card-label accent-4">寻访渠道</p>
        <ul>
          <li><strong>英伟达 Isaac 团队现任/前成员</strong>是最高优先级目标</li>
          <li>Josh Tobin（前OpenAI，域随机化论文一作）前同事圈</li>
          <li><strong>会议</strong>：ICRA仿真到真实专题、CoRL、RSS</li>
          <li><strong>领英</strong>："sim-to-real" OR "domain randomization" AND "robotics"</li>
        </ul>
      </div>
      <div>
        <p class="card-label accent-4">薪酬参考</p>
        <ul>
          <li>美国：年薪总包约 145-290万人民币</li>
          <li>国内：约 80-300万</li>
          <li>国内头部企业首席科学家级别薪资可达千万级以上</li>
        </ul>
      </div>
    </div>
  </div>
</section>

<!-- ROLE 5 -->
<section id="role5">
  <div class="section-header">
    <div class="section-num bg-accent-5">5</div>
    <div class="section-title">
      <h2>高级SLAM工程师</h2>
      <p>机器人的"空间感知系统" · 全球约2,000-3,000人 · 稀缺度 ★★★☆☆</p>
    </div>
  </div>

  <div class="grid-2">
    <div class="card">
      <h3><span class="accent-5">◆</span> 工作内容</h3>
      <ul>
        <li>视觉SLAM / 激光SLAM / 视觉惯性里程计算法开发</li>
        <li>多传感器融合（相机 + 陀螺仪 + 激光雷达）</li>
        <li>动态环境下的鲁棒定位</li>
        <li>三维语义地图构建</li>
        <li>多楼层、室内外无缝切换建图方案</li>
      </ul>
    </div>
    <div class="card">
      <h3><span class="accent-5">◆</span> 人形机器人SLAM的六大特殊挑战</h3>
      <ul>